分類目標與選題限制對於高階試題反應理論之電腦化分類測驗效能的影響
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(3) 506 Matlab. IRT. Matlab. 506. 2016 i. 6. 30.
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(5) high-order item response theory, HIRT computerized classification test, CCT Fisher Information HIRT-CCT HIRT. ability estimated-based,. confidence interval, ACI EB. Fisher Information. FI. FI2. FI1 FI1+2 15 30 60. 30. 60. 90. 120. HIRT-CCT. iii. 90 HIRT-CCT.
(6) FI. FI2 FI1. FI. FI1. FI2 FI1+2. FI2 FI1. FI 30 60 HIRT-CCT. HIRT-CCT. iv. FI1+2. FI1+2.
(7) The Influences of Target Classification Traits and Item Selection Constrains on the Efficiency of Computerized Classification Testing Using High-Order Item Response Theory Kuo-Feng CHANG Abstract This study aims to implement high-order item response theory (HIRT) in computerized classification test (CCT), and to investigate the influences of target classification traits, Fisher Information (FI) item selection methods, cutting points, maximum test lengths and item selection constrains on the efficiency of HIRT-CCT. In this study, 3PLM-HIRT was employed as the test model and the ability confidence interval with estimated-based item selection method was used as a classification method. Five independent variables were manipulated: (a) target classification traits target at second-order latent trait, target at first-order latent trait, and target at both second-order and first-order latent traits; (b) FI item selection methods maximum of FI at secondorder latent trait (FI2) , maximum of FI at first-order latent trait (FI1) , and maximum of FI at both second-order and first-order latent traits (FI1+2); (c) number of cutting points 1 and 2; (d) maximum test lengths 15, 30, 60, 90 for 1-cutting point and 30, 60, 90, 120 for 2-cutting point (e) item selection constrains no item exposure and content balancing controls, only item exposure control, only content balancing control, and item exposure plus content balancing controls. Five major dependent variables were included: (a) classification accuracy, (b) average test length, (c) maximum item exposure rate, (d) pool usage rate, and (e) content balancing (the percentage of selected items for each content). The main results are summarized as follows: 1. For three types of target classification traits, the results indicated that there was a little difference between target at first-order latent trait and target at both second-order and first-order latent traits. Besides, classification accuracy would increase while maximum test length increases. 2. For three types of FI item selection methods, in term of classification accuracy, FI2 had little effect on increasing classification accuracy of second-order latent trait. FI1 could increase classification accuracy of the first-order latent trait with the lowest factor loading (the second highest factor loading one would keep unchanged or increasing), but the one with the highest factor loading would decrease. However, three methods tended to be similar while maximum test length increases. In term of v.
(8) the percentage of forced classification, and average test length, using FI1 would yield the lowest percentage of forced classification, and the lowest average test length for target at first-order latent trait and target at both second-order and first-order latent traits; using FI2 would yield the lowest percentage of forced classification, and the lowest average test length for target at second-order latent trait. In term of content balancing, the results were close to being even while using FI1+2. Besides, there are more items selected from the highest factor loading item pool while using FI2, and more from the lowest factor loading while using FI1. However, the differences among three content balancings would decrease while maximum test length increases. 3. For four types of maximum test lengths, the percentage of forced classification would decrease but classification accuracy, average test length, and pool usage rate would increase while maximum test length increases. 4. For two types of cutting points, classification accuracy would decrease but the percentage of forced classification, average test length, and pool usage rate would increase while cutting point increases. 5. For item selection constrains, although item exposure control could control item exposure rate, it would result in a slight decreasing on classification accuracy, a slight increasing on the percentage of forced classification, and average test length, but a substantial increasing on pool usage rate. As for content balancing control, although it could maintain an even content balancing, it would lead to no differences occurred to the results among the three methods. In sum, three types of target classification traits of HIRT-CCT would have the best performances in the context of 1-cutting point while setting maximum test length to 30 and using FI1+2; as for the context of 2-cutting point, HIRT-CCT would yield the best performances while setting maximum test length to 60 and using FI1+2. Besides, imposing item exposure and content balancing controls on HIRT-CCT not only could control item exposure rate and maintain an even content balancing, but also improve pool usage rate; moreover, it brought little effect on the efficiency of HIRT-CCT. Keywords: high-order item response theory, computerized classification testing, target classification traits, item selection constrains. vi.
(9) ................................................................................................................................ i .......................................................................................................................... iii Abstract ............................................................................................................................. v ................................................................................................................................. vii .................................................................................................................................. ix ................................................................................................................................ xiii ..................................................................................................................... 1 ......................................................................................... 1 ..................................................................................................... 3 ..................................................................................................... 4 ............................................................................................................. 7 ..................................................................................... 7 ....................................................................................... 20 ........................................................................................................... 31 ........................................................................................... 31 ........................................................................................... 38 ............................................................................................... 41 ................................................................... 41 ................................................................... 78 ..................................................................................................... 109 ................................................................................................. 109 ................................................................................................. 112 ....................................................................................................................... 115 ............................................................................................................... 115 ............................................................................................................... 115 vii.
(10) viii.
(11) 4-1-1. 1 ...................................................................................................................... 51. 4-1-2. 1 .................................................................................................................. 52. 4-1-3. 1 ...................................................................................................................... 52. 4-1-4. 1 .................................................................................................................. 53. 4-1-5. 1 ...................................................................................................................... 53. 4-1-6. 1 .............................................................................. 54. 4-1-7 1 .................................................................................. 60 4-1-8 1 .......................................................................... 61 4-1-9. 1 .............................................................................. 61. 4-1-10. 1 ..................................................................... 62. 4-1-11. 1 ............................................................................. 62. 4-1-12. 1 ................................. 63 ix.
(12) 4-1-13. 1 ......................................................................................... 67. 4-1-14. 1 ................................................................................. 68. 4-1-15. 1 ..................................................................................... 68. 4-1-16. 1 ................................................................................. 69. 4-1-17. 1 ......................................................................................... 69. 4-1-18. 1 ............................................. 70. 4-1-19. 1 ......................................................................................... 74. 4-1-20. 1 ................................................................................. 75. 4-1-21. 1 ..................................................................................... 75. 4-1-22. 1 ................................................................................. 76. 4-1-23. 1 ......................................................................................... 76. 4-1-24. 1 ............................................. 77. 4-2-1. 2 ...................................................................................................................... 83 x.
(13) 4-2-2. 2 .................................................................................................................. 84. 4-2-3. 2 ...................................................................................................................... 84. 4-2-4. 2 .................................................................................................................. 85. 4-2-5. 2 ...................................................................................................................... 85. 4-2-6. 2 .............................................................................. 86. 4-2-7 2 .................................................................................. 90 4-2-8 2 .......................................................................... 91 4-2-9 2 .............................................................................. 91 4-2-10. 2 ..................................................................... 92. 4-2-11. 2 ............................................................................. 92. 4-2-12. 2 ................................. 93. 4-2-13. 2 ......................................................................................... 97. xi.
(14) 4-2-14. 2 ................................................................................. 98. 4-2-15. 2 ..................................................................................... 98. 4-2-16. 2 ................................................................................. 99. 4-2-17. 2 ......................................................................................... 99. 4-2-18. 2 ........................................... 100. 4-2-19. 2 ....................................................................................... 104. 4-2-20. 2 ............................................................................... 105. 4-2-21. 2 ................................................................................... 105. 4-2-22. 2 ............................................................................... 106. 4-2-23. 2 ....................................................................................... 106. 4-2-24. 2 ........................................... 107. xii.
(15) 2-1-1. UIRT................................................................................................... 12. 2-1-2. MIRT ...................................................................................................... 12. 2-1-3. UIRT................................................................................................... 13. 2-1-4. IRT ..................................................................................................... 13. 2-1-5 HIRT ............................................................................................................... 13 4-1-1. ..................... 44. xiii.
(16) xiv.
(17) hierarchical structure. higher-order. lower-order. overall. ability. domain ability PISA The Programme for International Student Assessment. quantity and relationships. space and shape. change. uncertainty. 4. test of Chinese as a foreign language, TOCFL . ETS. test of. English as a foreign language, TOEFL 1. high-order item response theory, HIRT 1. de la.
(18) Torre & Douglas , 2004 Sheng & Wikle, 2008 Wang,. Chen, 2010. Huang, Wang, Chen,. de la Torre & Song, 2009. Huang,. Su, 2013. TOEFL high. intermediate. low. criterion-referenced. computerized classification test, CCT HIRT-CCT HIRT-CCT. HIRT-CCT. HIRT-CCT. 2.
(19) HIRT. CCT. HIRT-CCT Fisher Information. Fisher Information. 15 30 60 120. 90. 30 60 90. HIRT-CCT CCT. 1. 3. HIRT. 3. ACI + EB.
(20) Fisher Information. 15 30 60. 90. 30 60 90. 120. HIRT-CCT. HIRT-CCT. HIRT-CCT Fisher Information. HIRT-CCT. HIRT-CCT HIRT-CCT HIRT-CCT. Fisher Information. HIRT-CCT. Fisher Information. high-order item response theory. HIRT. hierarchical. structure overall ability. domain. ability linear function 4.
(21) . computerized classification test CCT. mutually. exclusive. multiple. Target Classification traits. item selection constrains. CCT. .2 i. 1000. 200. 3. 900 300. B. 1/3. 300. C 5. 300. A.
(22) 6.
(23) item response theory, IRT IRT unidimensional item response theory, UIRT multidimensional item response theory, MIRT high-order item response theory, HIRT. UIRT. unidimensionality. local independency. IRT likelihood function. dichotomous parameter logistic model, 1PLM . Rasch. #(%&' = 1 *' , ,& ) = *' parameter # %&' = 1. ,&. j %&' . j j. UIRT Rasch, 1960. exp (*' − ,& ) 1 + exp (*' − ,& ). item difficulty 1. i 7. 1PLM. 2.1. i i. one-. 0.
(24) two-parameter logistic model, 2PLM. Birnbaum, 1968. item discrimination parameter 2PLM #(%&' = 1 *' , 2& , ,& ) = *' %&' . j j. 2.2. 1 + exp [2& *' − ,& ]. 2&. j. #(%&' = 1). exp [2& *' − ,& ]. ,&. i i. i. 1. 0. i. three-parameter logistic model, 3PLM Birnbaum, 1968 item guessing parameter. 3PLM. #(%&' = 1 *' , 2& , ,& , 5& ) = 5& + *' . 2&. j 5&. ,&. %&' 0 #(%&' = 1). j. i i partial credit. Masters, 1982. 1978. rating scale model, RSM. Andrich,. nominal response model, NRM Bock, 1972. grade response model, GRM Samejima, 1969 1992 . i. j. polytomous model, PCM. 2.3. 1 + exp [2& *' − ,& ] i. i. 1. exp [2& *' − ,& ]. 1 − 5&. PCM. Muraki. generalized partial credit model, GPCM. PCM. Kelderman, 1996 8.
(25) UIRT UIRT. MIRT MIRT. UIRT between-item multidimensional test. within-item multidimensional test. Adams, Wilson, & Wang, 1997. multidimensional one-parameter logistic model, M1PLM Mckinley & Reckase, 1982 . #(%&' = 1 6' , ,& ) = 6' %&' . j j. exp (6' − ,& 7) 1 + exp (6' − ,& 7). ,&. j. M1PLM. 2.4 7. i. i. 0 # %&' = 1. 1. i M1PLM. 1PLM. multidimensional two-parameter logistic model, M2PLM Mckinley & Reckase, 1983. M1PLM *'. 2&. 6'. 8&. M2PLM #(%&' = 1 6' , 8& , ,& ) = 6' . 8& . j %&' . j. i. 9. exp [8& 6' − ,& ] 1 + exp [8& 6' − ,& ]. 2.5 ,&. i 1. i 0.
(26) # %&' = 1 . j. i M2PLM. 2PLM. multidimensional three-parameter logistic model, M3PLM Hattie, 1981. M2PLM M3PLM. #(%&' = 1 6' , 8& , ,& , 5& ) = 5& + 6' . ,&. i. 5&. i. 2.6. 1 + exp [8& 6' − ,& 7 ]. 8&. j 7. j. exp [8& 6' − ,& 7 ]. 1 − 5&. 9. i. %&' 0 # %&' = 1. 1. j. i Adams Wilson. Wang 1997. multidimensional random coefficients multinomial logit model, MRCMLM. Rasch. MRCMLM. #(%&': = 1 6' , ;, <, =) =. %&': 0. j. i. # %&': = 1. exp >&: 6' − 8&: ; 1+. 1 i. k. 6' =. k. j. ;. D. (EA , EB , … , EF ) i. G&. P 8&:. 2.7. >&: 6' − 8&: ;. k. j. *'A , *'B , … , *'D . :? :@A exp. i=1,2,...,n. k=1,2,…,k. design vector. i P. ; 10. k.
(27) design matrix (8&A, 8&B,…, 8&: ). >&:. i=1,2,...,n. A. A. <7 , <H,…, <I. k=1,2,…,k. i. scoring vector. k 6. D. B =7 , =H,…, =I. scoring matrix B MRCMLM. =I = (>&A, >&B,…, >&: ). IRT. 1960. <I =. Rasch. Rasch,. logistic latent trait model, LLTM Fischer, 1973. Andrich, 1987. RSM. PCM Masters, 1982. MRCMLM ConQuest Wu, Adams, & Wilsons, 1998. hierarchical structure overall ability domain ability HIRT 3. 1 IRT. Wang, Chen, & Su, 2013. Huang,. 2-1-1. consecutive UIRT. UIRT UIRT. 11.
(28) . 2-1-1. UIRT 2-1-2. 2-1-2. between-item MIRT. Wang, 1997. MIRT. Adams, Wilson, &. MIRT Wang,. Chen,. Cheng, 2004. MIRT. Huang, Chen. Wang, 2012. MIRT. MIRT composite scores. 2-1-3. Adams, Wilson, & Wu, 1997. composite UIRT. Huang et al., 2013 12. Ackerman.
(29) 1991. UIRT. biased . Wang. local item dependence & Wilson, 2005a Wang & Wilson, 2005b 2-1-4. Wang, Cheng, & Wilson, 2005 Bi-factor IRT IRT. 3. Sheng β. HIRT. 1. testlet. response models Wainer, Bradlow, & Wang, 2007 2-1-5. Wikle 2008. HIRT. IRT. IRT. . 2-1-3. UIRT. 2-1-4. IRT 13. . 2-1-5 HIRT.
(30) HIRT. de la Torre. Douglas. cognitive diagnosis Wikle. 2004. HIRT model. 2008. IRT. Sheng Bayesian. hierarchical multidimensional IRT model. IRT. IRT IRT. la Torre. de. Song 2009. three-parameter logistic. high-order IRT model. IRT de la Torre. IRT. Hong 2010. IRT. IRT. models. nonhierarchical IRT. de la Torre, Song. 2011. Hong. HIRT. HIRT. Huang, Wang. IRT Huang. UIRT. Chen 2010. 2013 1PLM 2PLM. 3PLM. PCM. Andrich, 1978. Masters, 1982. GPCM. IRT. CAT. HIRT. HIRT. RSM. Samejima, 1969. GRM. Wang 2012. Muraki, 1992. testlet HIRT-CAT. multilevel HIRT 14. Huang Huang. Wang. Huang 2012 2013. HIRT.
(31) Huang. 2010. HIRT. (2). (A). * K . linear function. (A). (B). *'M = NM *' j NM. j. v. *'M. (A). + O'M. 2.8. measures of association. v. regression weight (1). OKP . factor loading *. residuals. O. N. 0, 1. 2.8 quadratic function. cubic function. Huang et. al., 2010 3PLM (A). #'&QM = 5&M +. #'&QM ,&M. 1 − 5&M. j. exp [2&M *'M − ,&M ] 1 + exp [2&M. v. i. 5&M. HIRT. (A) *'M. 2.9. − ,&M ] 2&M. 1 2.8. 2.9. 3PLM-HIRT (B). #'&QM = 5&M +. 1 − 5&M. 5&M = 0 2.10. exp [2&M NM *'. (B). 1 + exp [2&M NM *'. 2.10. 2PLM-HIRT. 1PLM-HIRT. HIRT. confirmatory. 15. (A). − ,&M + O'M ]. 2.10. (A). − ,&M + O'M ] 5&M = 0. 2&M = 1. dimensionality.
(32) computerized adaptive testing, CAT . Sand, Water, & Mcbride, 1997 Wainer, Dorans, Flaugher, Green, Mislevy, Stenberg, & Thissen, 1990 Weiss, 1985. HIRT. CAT. HIRT-CAT Huang et al., 2012 CCT. CCT MCAT. Segall, 1996. HIRT. HIRT. 1. 3. model identification 3. 0 residual. (1). 1. (1). (1). * (B) , O1 , O2 , O3. 0. r. s ^ _,` (S). WA/B. exp[− Z. 2.12. diagonal matrix. 1 − NBB. 1 − NRB. S ≡. multivariate normal distribution. g S = (2V)WX/B Z ]. 1 − NAB. 1. 2.13 r. A B. S−[. 1. \. 1 − NAB. I(S). Z WA (S − [)] 1 − NBB. 2.11. 1 − NRB ^ _,` (S). s = 1, 2 ,3 ,4. 2.14 ]≡. 0, 0, 0,0 16. 2.12.
(33) 1 Z≡. 0 1 − NAB. 0 0 1 − NBB. 0 0 0 1 − NRB. 2.13. e. ^ _,` (S) 2_& v. −. 2b9 2c9 (1−#9dP )(#9dP −59P )(59P #9dP −#9dP ) 2. #9dP (1−59P ). 2`&. i. i. r. #&QM. s. 5&M. 1. 2.14. 2. candidate determinant 2.15. f& (S) ≡ ^ : (S) + ^ & (S) + Z WA ^ : (S). k. ^ & (S). Fisher Information. Fisher Information Yao 2012 f& (S). 2.15 CAT. g: = %A , %B , … , %:. k. likelihood function. h S g . prior distribution 2.11. g S. posterior distribution. g Sg. maximum a posterior. procedure, MAP log. Newton-Raphson procedure p. 17. -.
(34) i iS. ln g. i ln m iθ1 i ln m iθ2. Sg Sg. . . . i ln m S g. Sg =. =0. 2.16. iθo. p pqo. ln m S g. . 2G9 (#9dP −59P )(r9 −#9dP ) i − S iθ o (1−59P )#9dP. pe. pe. pqt. pqt pqe. e ln m S g . ue. J (S) = . &@:. uqet ue. ln m S g. e ln m S g. uqt ue. e ln m S g. uqt. . pe. pqee ue. ue. ln m S g. uqt qv. ln m S g . ue. uqt qv ue. e ln m S g. uqt. uqt qv. ue. ue. uqt. uqet. e ln m S g. ⋯ m. Z−1 S − [. T. pe pqt pqy pe. ⋯ m pq ⋱ m. e pqy ue. uqt qv. ln m S g . pe. pqey. 2.17. ln m S g ln m S g. 2.18. ⋮ m S g. ln m S g. r, s {. iB ln m S g iθ_ iθ` } _`. =. Z WA. 2_& 2`& (1 − #&QM )(#&QM − 5&M )(5&M r& − #&QM B ) #&QM B (1 − 5&M )B. & | :. r S(~). S('). 2.19. s. = S(~WA) − (~). 2.20 (~). g. (~). − } _`. i ln m S g iθ i2 ln m S g iθiθ. S(~) . 2.21 S(~). 0.001 18. 2.21. (~).
(35) MAP. 3 (A). (B). (A). 6'M = ÄM *'. + Å'M (A). j. S'. (B). (A). θ'. Ä =. É'. ≡. (A). 2.22 (A). ≡. (A). ÑWA :. Fisher. G Ñ :. − {[ Ö SÜ ]. Ö SÜ. =−. T. T. (A). O'A , O'B , O'R. 2.18. á_` = −{. (A). T. βA , βB , βR. 2.23. (A). θÇA , θÇB , θÇR. 2.23. Ñ. iB ln m S g iθ_ iθ`. =−. àâ? (6) àâ? (6) × àäã àäç. & | : F (6)(AWF (6)) ? ?. 2_& 2`& 1 − #&QM #&QM − 5&M 5&M #&QM − #&QM B #&QM B 1 − 5&M. & | :. B. + } _`. + }bc. 2.24. ÑWA : . SE ≡. square root. (1). (1). (1). θ(2) , ε1 , ε2 , ε3. 2.23. SE è{ θ V1. =. 1 βB [è{ *(2) ]B + è{ ε V. CCT 2.26. 2.22 2.27. 19. 2.25. B. 2.25. T.
(36) CCT mutually exclusive multiple CCT CCT CCT CCT CCT. CCT CCT. CCT. high-stakes. CCT round testlet test termination criterion. 20.
(37) maximum test length. CCT CCT. Spray &. Reckase, 1994 CCT CCT. CCT Kingsbury. random Weiss. Ferguson, 1969. 1983. adaptive item. selection CCT estimated-based, EB CB. cut point-based, Fisher Information. 1. EB Fisher Information. 21.
(38) Weiss. Kingsbury 1979. EB. ACI. ACI standard error of measurement EB Kingsbury & Weiss, 1983. Weiss & Kingsbury, 1984. Thompson, 2009. 2. Spray. Reckase 1994. CB. EB. CB EB. Eggen, 1999 Eggen & Straetmans, 2000 3. ACI. EB. ACI. Thompson, 2009. CB ACI EB. 1 ACI EB. ACI CB. CAT. * ± 100 1 − í % CI *ì. CAT. 100 1 − í % CI * ±100. 1−í. % CI. 2 ACI CB CAT 22.
(39) * ± 100 1−í. *ì. % CI. CAT. 100 1 − í % CI * ± 100 1 − í % CI. ACI EB. Thompson, 2009. Eggen & Straetmans, 2000. ACI EB. ACI EB. CCT. test termination criterion. ability confidence interval, ACI Thompson, 2009. adaptive mastery testing. Kingsbury & Weiss, 1983. sequential probability ratio test, SPRT Wald, 1947. Reckase, 1983. Bayesian decision theory, BDT Lewis & Sheehan, 1990 Eggen Spray Smith. Lewis. Straetmans 2000. 1993 1995. ACI. SPRT BDT. ACI ACI Kingsbury. Weiss 1983 *. ACI confidence interval, CI 23.
(40) ACI * ± 100 1 − í % CI. *ì 1−í. 100 * ± 100 1 − í. *ì. % CI. * − 100 1 − í % CI í. % CI. *ì. * + 100 1 −. *ì. % CI S 1. * ≤ *A − ïñ è{ *, ó. 5+1. . è. *ì + ïñ è{ *, ó < * ≤ *ìôA − ïñ è{ *, ó. 2.26. * > *õWA + ïñ è{ *, ó. *. *ì. ïñ. normal deviate è{ *, ó. 5 c =1, 2, 3, …, S-1. 1−í. 100. % CI. ó. í. *. ACI. 1. . 5 + 1 è. * ≤ *A *ì < * ≤ *ìôA. 5 = 1,2,3, … , è − 1. * > *õWA 1 *A 1 *A. 1 2. *B. 2. è − 1 *õWA. S. 24. 2.27.
(41) multiple. ETS. TOEFL high. Spray. imtermediate. low. Reckase 1994. Spray, 1993. CCT. item selection. constraints. 25.
(42) 1. content balancing . content validity. item bank security. CCT. content representation. Kingsbury & Zara, 1989. Kingsbury & Zara. the weighted deviations model. multinomial model Ankenmann. Stocking & Swanson, 1993. MM Chen, Ankenmann, & Spray, 2003. 2004. MMM. WDM. MM. the Chen. the modified multinomial model. MMM. MMM. cumulative distribution. 1. multinomial distribution j. CCT. U r&. 0, 1. cumulative probability A. 1/3. A. 0.333 + 0.333 A r& ≤ 1. B. B. C. 1 0.333 + 0.333 + 0.334 0.333 ≤ r& < 0.666 C. 26. C 0.333. 0.666. 0 ≤ r& < 0.333 B. 0.666 ≤.
(43) i. j. j. CCT 2. maximum item exposure rate CAT. CCT. Davey & Paeshall, 1995 Martin, 1983. Sympson & Hetter, 1985. McBride &. van der Linden, 1998. the Sympson and Hetter procedure. SH. Sympson & Hetter, 1985 SH 9. 1. 2 #& A . 9. #& S . 3 #& A S . 9 bûü† #& A = #& A S × #& S ≤ bûü† #& S > bûü† bûü†. #& A S . #& A S . bûü† / #& S SH. CAT. 27. 2.28 #& S ≤.
(44) bûü† 1. i. U 0, 1 #& A S . #& (S) #& A #& S > bûü† #& S ≤ bûü†. bûü†. #& S #& A S = 1 #& A S =. #& A S. K #& A S . 2.29. 1. #& A S bûü† + ε ε SH Chang & Ansley, 2003. SH. Chen, Ankenmann, & Spray, 2003 Ju, 2005 Wu & Chen, 2008 28.
(45) Ju 2005. SH. SH. the SH_online procedure,. SHO Chen the freeze with Freeze. SHOF. Revuelta & Ponsoda, 1998. Liao 2005. SHO. the SHO procedure. the freeze. freeze SHOF. 2008. SHOF CCT SHOF. CCT bûü† 1 SH. j 1/3 #& S. j #& (A). #& A S #& A S . j+1. #& ° > bûü†. #& A S = 0. #& ° ≤ bûü† . #& S ≤ bûü†. #& ° ≤ bûü† . #& S > bûü†. #& A S = 1 bûü† #& A S = #& S. ¢ûü†. #& A S . #& A S . 29. 1. 2.30.
(46) 1/3 #& A S K+1. ¢ ¢£2r. 30. 1.
(47) ACI EB Fisher Information HIRT-CCT. HIRT-CCT. 3PL-HIRT. (3). 1. 3. (1) (A). (A). *A. *B. A . *. 2. (2) 3. *R. 0.9. 0.8. ACI EB. 0.7 MCAT 1. 0. 3. MAP * ± 100 1 −. í. % CI. *ì. MCAT. 100 1 − í % CI * ± 100 1 − í % CI. 31.
(48) Fisher Information 288. 3 × 3 × 2 × 4 × 4 Target Classification traits. S. HIRT 1. (B). *'. (B). *ì + ïñ è{ * (B) , ó < *'. 5+1 è. ≤ *A − ïñ è{ * (B) , ó. (B). *'. ≤ *ìôA − ïñ è{ * (B) , ó. > *õWA + ïñ è{ * (B) , ó 3.1. (B). *' . ïñ. K. *5. normal deviate è{ * (B) , ó. 100. 5 c =1, 2, 3, …, S 1 1−í. % CI. í. ó. 1. (B). *'. (B). 5 + 1 è. ≤ *A. *ì < *' (B). *'. > *õWA. 32. ≤ *ìôA. 3.2.
(49) 3 3 3. S. HIRT 1 5+1 è. 3. 3 (A). (A). *'M ≤ *A − ïñ è{ *M , ó (A). (A). (A). *ì + ïñ è{ *M , ó < *'M ≤ *ìôA − ïñ è{ *M , ó (A). (A). *'M > *õWA + ïñ è{ *M , ó 3.3. (A). *'M . K. P. P = 1, 2, 3. c =1, 2, 3, …, S 1 ïñ. c. 100 1 −. normal deviate (1). í % CI í. è{ *P , ó. *ì. ó. P. (A). *'M ≤ *A. 1. 5 + 1. (A). *ì < *'M ≤ *ìôA. 3.4. (A). è. *'M > *õWA. 4 1. 3 4. 4. 4. 33. 1. 3.
(50) S. HIRT. 3-1. 3-2. 3-3 3-4. Fisher Information. Fisher Information item selection methods. cutting points. criterion referenced. norm referenced. 34.
(51) 4. 1. 0.525 0.525. 0.525. 30. 0.525. 70 ± 0.525. 4 0.525 40. 3. 0.525. 30. ± 0.525 ± 0.525. 30%. maximum test length CCT. CCT. 15 30 60 30. 60. 90. 90. 120. item selection constraints 4 1. 2 3. 4. 35.
(52) the Sympson and Hetter procedure with the online and freeze method. SHOF. Chen, Lei, & Liao, 2008. maximum item exposure rate. 0.2. 20. the modified multinomial model . MMM. Chen. & Ankenmann, 2004 1/3. 1/3. FI. classification accuracy, CA. 1000. §°. n. §° =. 36. ó •. N. 3.5.
(53) average test length, ATL 1000 °¶h. •. K. °¶h =. ß '@A ¢'. 3.6. •. maximum item exposure rate. 1000. i. 200. b&. ℎ& . M. i. 0.2. i. N. 900. b& =. 900. ℎ& , 9 = 1,2,3, … , © •. 3.7. pool usage rate, PUR. #™´. m. M. #™´ =. 37. £ ©. 3.8.
(54) content balancing, CB. 1000 1000. 3 1000 §¨. N. K. P ß '@A ¢'M ß '@A ¢'. §¨M =. 3.9. , P = 1,2,3. Matlab 900 U -3.0, 3.0. N 0, 0.25. 0.1. U 0, 0.3 300 N 0, 1. 1000. 3PL-HIRT U. 0, 1. ACI + EB. MAP 100. 1−í. % CI 100. 1 − í % CI. α = .05 38.
(55) 288. 20. replications. sampling variability. 20. CCT. SHOF MMM. 39.
(56) 40.
(57) . 1. 4-1-1 80%. = 15. FI. 3. .84 .83. .88. .90. .89. 90 3. .94. 80% 41. .86. .91.
(58) = 15 .83. FI. .85. 90. .88. 3. 80%. = 15. FI. .89. .82. 90. .92. 2.25. 3. = 15 1. .86 .87 .86 .88 90 .88. .93. .93. .93. .93. .93. .93. Fisher Information. FI1+2 3. .85 .87 .86 .88. .88. .94. FI1+2 42.
(59) FI1. FI2 = 15 FI2. 1%. 3. [0.9]. 3%. [0.7]. [0.8] 3%. [0.9] 2.15 [0.9] i. 3. 1 0.9 0.8. 0.7 0. 1. 0. [0.9] 2.20 2.16. [0.8] [0.7]. 2.12. [0.9] [0.7] 2.15. 90. FI2. FI1+2. FI2. [0.9] .88 3. 2% = 15 FI1. 1%. [0.9]. 3 4%. [0.8] =. 43.
(60) 60. 1%. [0.7]. 1%. [0.7] [0.7] i 1 0.9 0.8. 3. 0.7 0. 1. 0. [0.9] 234.95. [0.8]. 239.82. [0.7]. 244.14 [0.7]. 4-1-1. [0.9]. [0.8]. [0.7] [0.9]. 90 FI1. FI1+2. FI1. [0.7] 1% 7Ø. ∞± Ø Ø. Ø ≤. ≤≥ Ø. [0.9]. 3. Ø Ø ¥. µH = H¥∂. µ≤. 7Ø. ≤¥ Ø Ø. Ø ≤. ±7 Ø. [0.8]. Ø Ø ¥. µH = H¥µ. ±H. 7Ø. ≤¥ Ø Ø. Ø ≤. ≤≥ Ø. Ø Ø ∂. 7∞ = H∂∂. 7∂. [0.7]. 4-1-1 = 15 FI2 44. FI1.
(61) FI2 FI1. [0.7]. [0.8]. [0.9]. 1. 4-1-2 1. = 15 .45. .49. FI 90. .20. 3. FI1+2 .82 .74 .65 .62 .82 .73 .66 .61 FI FI1. FI2. FI1+2. FI1. FI1 FI2 FI1. FI1+2. FI2 45. .21.
(62) FI2 FI1. FI1+2. FI2. 3 FI1+2 3 FI1 FI1+2. FI1. FI1. FI1+2. 3% FI. 15 30 60 .99. .94. 90. 1.00. .97 .99. 1. 1.00. 4-1-3 FI 1 = 46.
(63) 15. 9.68 29.73. 10.82. 90. 31.61. 3. FI1+2 13.44 45.32 64.73. 24.91. 13.48 24.79 45.63 64.28. FI FI1. FI2. FI1+2. FI1. FI1 FI2 FI1+2. FI1. FI2. FI2. FI1. FI1+2. FI2 3 FI1+2. 3 FI1 47.
(64) FI1+2 FI1 1.58. 1. 4-1-4 FI 1. 1. 4-1-5 1. = 15 .05 .23. .06. 90. .26. 3. FI1+2 .07. .14. .26. .07 .14 .26 .35 .08 .08 .13 .22. .13. .34 FI2. .23. .31. .31 48. FI.
(65) FI. FI1. FI1+2 2%. FI1. FI1+2. FI2. 1. 4-1-6. FI. FI1+2 = 15. FI1+2 .33 .31 .36. 1/3. Yao 2012. 2.15 CAT f& (S). FI2. [0.9]. [0.9] 2.15 [0.9]. [0.7] 2.15. FI1. [0.7]. [0.7] 49.
(66) 2.15. [0.7] [0.9]. 1 = 15 80%. FI. FI2 FI1. [0.7]. [0.8]. [0.9]. FI1. FI2. FI1+2. FI2 FI1. FI1+2. FI1+2. FI2 FI1. [0.9] [0.7]. 50. FI.
(67) 4-1-1. 1 FI 1+2. MTL. [. ]. FI 2. FI 1. FI 1+2. Mean. SD. Mean. SD. Mean. SD. (1) [0.9] (2) [0.8] (3) [0.7]. .85 .87 .86 .88. .01 .01 .01 .01. .86 .90 .83 .85. .01 .01 .01 .01. .84 .83 .86 .89. .01 .01 .01 .01. .85 .64 .40 .47. (1) [0.9] (2) [0.8] (3) [0.7]. .87 .89 .90 .90. .01 .01 .01 .01. .87 .92 .87 .87. .01 .01 .01 .01. .86 .88 .90 .91. .01 .01 .01 .01. (1) [0.9] (2) [0.8] (3) [0.7]. .88 .92 .91 .92. .01 .01 .01 .01. .88 .93 .91 .90. .01 .01 .01 .01. .88 .91 .92 .92. (1) [0.9] (2) [0.8] (3) [0.7]. .88 .93 .93 .93. .01 .01 .01 .01. .88 .94 .93 .91. .01 .01 .01 .01. .89 .93 .93 .93. 15. 30. 60. 90. FI 1+2 = . Mean SD. FI 2. FI 1. FI 1+2. FI 2. FI 1. Mean. SD. Mean. SD. .01 .01 .02 .02. .86 .70 .37 .36. .01 .01 .02 .01. .83 .55 .60 .61. .01 .02 .02 .02. .86 .87 .86 .88. .01 .01 .01 .01. .86 .89 .82 .84. .01 .01 .01 .01. .84 .83 .86 .89. .01 .01 .01 .01. .87 .57 .33 .41. .01 .01 .01 .02. .87 .63 .32 .27. .01 .02 .01 .01. .86 .49 .53 .52. .01 .02 .01 .02. .87 .90 .89 .90. .01 .01 .01 .01. .87 .91 .87 .88. .01 .01 .01 .01. .87 .88 .90 .90. .01 .01 .01 .01. .01 .01 .01 .01. .88 .54 .30 .36. .01 .01 .02 .01. .88 .58 .29 .23. .01 .01 .01 .01. .88 .45 .49 .48. .01 .02 .01 .01. .88 .92 .91 .92. .01 .01 .01 .01. .88 .93 .91 .90. .01 .01 .01 .01. .87 .91 .92 .92. .01 .01 .01 .01. .01 .01 .01 .01. .88 .52 .29 .35. .01 .02 .02 .01. .88 .56 .28 .21. .01 .01 .01 .01. .88 .44 .47 .46. .01 .01 .01 .02. .88 .93 .93 .93. .01 .01 .01 .01. .88 .94 .92 .92. .01 .01 .01 .01. .88 .92 .93 .93. .01 .01 .01 .01. FI 2 = . Mean SD Mean SD Mean SD. FI 1 = . MTL = . 51.
(68) 4-1-2 MTL. 1 FI 1+2. FI 2. FI 1. FI 1+2. FI 2. FI 1. FI 1+2. FI 2. FI 1. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. 15. .82. .01. .88. .01. .79. .01. .47. .01. .45. .01. .49. .02. .82. .01. .89. .01. .79. .01. 30. .74. .01. .82. .01. .72. .01. .33. .01. .32. .01. .33. .01. .73. .01. .82. .01. .72. .01. 60. .65. .01. .69. .01. .65. .01. .24. .01. .24. .01. .24. .01. .66. .01. .69. .01. .64. .01. 90. .62. .01. .63. .01. .60. .01. .21. .01. .20. .01. .20. .01. .61. .01. .62. .01. .60. .01. FI 1+2 = . FI 2 = . FI 1 = . MTL = . 4-1-3. MTL. 1. FI 1+2. FI 2. FI 1. FI 1+2. FI 2. FI 1. FI 1+2. FI 2. FI 1. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. 15. 13.44. 0.09. 13.89. 0.09. 13.17. 0.08. 9.95. 0.16. 9.68. 0.11. 10.82. 0.12. 13.48. 0.09. 13.93. 0.07. 13.12. 0.08. 30. 24.91. 0.23. 26.73. 0.28. 24.35. 0.26. 15.66. 0.26. 15.40. 0.21. 16.77. 0.18. 24.79. 0.22. 26.73. 0.16. 24.50. 0.25. 60. 45.32. 0.50. 48.93. 0.42. 44.72. 0.51. 24.09. 0.59. 23.52. 0.62. 25.80. 0.65. 45.63. 0.46. 48.91. 0.36. 44.47. 0.55. 90. 64.73. 0.81. 68.57. 0.74. 63.15. 0.90. 31.14. 0.94. 29.73. 0.92. 31.61. 0.81. 64.28. 0.94. 68.27. 0.53. 63.14. 0.88. FI 1+2 = . FI 2 = . FI 1 = . MTL = . 52.
(69) 4-1-4 MTL. 1 FI 1+2. FI 2. FI 1. FI 1+2. FI 2. FI 1. FI 1+2. FI 2. FI 1. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. 15. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 30. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 60. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 90. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. FI 1+2 = . FI 2 = . FI 1 = . MTL = . 4-1-5 MTL. 1 FI 1+2. FI 2. FI 1. FI 1+2. FI 2. FI 1. FI 1+2. FI 2. FI 1. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. 15. .07. .00. .08. .00. .07. .00. .06. .00. .05. .00. .05. .00. .07. .00. .08. .00. .07. .00. 30. .14. .00. .13. .00. .14. .00. .10. .00. .09. .00. .11. .00. .14. .00. .13. .00. .14. .00. 60. .26. .01. .23. .01. .25. .00. .19. .01. .17. .00. .18. .01. .26. .01. .22. .00. .25. .00. 90. .34. .01. .31. .01. .34. .01. .26. .01. .23. .01. .25. .01. .35. .01. .31. .00. .33. .00. FI 1+2 = . FI 2 = . FI 1 = . MTL = . 53.
(70) 4-1-6 MTL. 15. 30. 60. 90. 1. [. ]. FI 1+2. FI 2. FI 1. FI 1+2. FI 2. FI 2. FI 1. Mean SD. Mean SD. Mean SD. SD. Mean. SD. Mean. SD. A [0.9]. .33. .00. .72. .00. .16. .00. .34. .00. .74. .00. .14. .00. .33. .00. .72. .00. .16. .00. B [0.8]. .31. .00. .17. .00. .34. .00. .31. .00. .14. .00. .34. .00. .31. .00. .17. .00. .34. .00. C [0.7]. .36. .00. .11. .00. .50. .00. .35. .00. .12. .00. .52. .00. .36. .00. .11. .00. .50. .00. A [0.9]. .34. .00. .67. .00. .22. .00. .35. .00. .69. .00. .20. .00. .34. .00. .67. .00. .22. .00. B [0.8]. .33. .00. .21. .00. .36. .00. .33. .00. .18. .00. .36. .00. .33. .00. .21. .00. .36. .00. C [0.7]. .33. .00. .12. .00. .42. .00. .33. .00. .13. .00. .44. .00. .33. .00. .12. .00. .41. .00. A [0.9]. .33. .00. .56. .00. .27. .00. .34. .00. .61. .00. .24. .00. .33. .00. .57. .00. .27. .00. B [0.8]. .34. .00. .29. .00. .36. .00. .34. .00. .26. .00. .36. .00. .34. .00. .29. .00. .36. .00. C [0.7]. .33. .00. .15. .00. .38. .00. .32. .00. .14. .00. .40. .00. .33. .00. .15. .00. .38. .00. A [0.9]. .33. .00. .54. .00. .28. .00. .34. .00. .58. .00. .26. .00. .33. .00. .54. .00. .28. .00. B [0.8]. .34. .00. .30. .00. .35. .00. .34. .00. .27. .00. .35. .00. .34. .00. .30. .00. .35. .00. C [0.7]. .33. .00. .16. .00. .37. .00. .32. .00. .15. .00. .39. .00. .33. .00. .16. .00. .37. .00. FI 2 = . SD Mean SD. FI 1+2. Mean. FI 1+2 = . Mean SD Mean. FI 1. FI 1 = . MTL = . 54.
(71) 1. 4-1-7. 1 SHOF. 1%. FI. 3. 3%. MMM. FI SHOF. MMM. FI2. [0.9]. FI1. [0.7]. [0.8]. FI2 [0.9]. [0.9] [0.8] [0.8]. [0.7]. [0.7]. FI1 [0.8]. [0.7]. [0.8]. [0.9]. [0.7]. [0.9] MMM 1/3. FI. FI FI1+2 SHOF 55. MMM MMM.
(72) . 1%. SHOF. MMM. MMM. FI. MMM FI1+2 SHOF. SHOF. MMM. MMM 1%. 2% 4-1-8. SHOF. FI. 5%. MMM. FI MMM. 1/3. FI. FI. FI. FI1+2. MMM. SHOF. MMM. 1% MMM. SHOF. MMM. FI. MMM. FI1+2 SHOF. MMM. SHOF. MMM. 4. 56.
(73) 15 30 60 .98. 90. 1.00. 2. 4-1-9. 1 SHOF. FI. = 90 MMM. FI. FI1+2 SHOF. 4.41. MMM. MMM. 0.21. MMM SHOF. MMM. FI. MMM FI1+2. SHOF. MMM. SHOF. MMM. = 90. 3.51. 3. 4-1-10. 1 SHOF .2 .87. .90. 57. MMM MMM.
(74) 4. 4-1-11. 1 SHOF. = 90 27%. MMM. FI. FI1+2 SHOF. MMM . MMM. 1%. MMM. SHOF. MMM. FI FI1+2. SHOF = 90. SHOF. MMM 21. 5. 4-1-12. 1 MMM 1/3. SHOF. FI2 FI1. [0.9] [0.7]. FI2 [0.9] [0.8]. 58. [0.7]. MMM.
(75) 6. 1 SHOF. MMM SHOF. MMM. FI. 59.
(76) 4-1-7. 1 SHOF. FI 1+2. MTL [. ]. MMM. FI 2. 11111. FI 1. SHOF. FI 1+2. FI 2. 11111 11111. FI 1. MMM. FI 1+2. FI 2. 11111 1. FI 1. Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD. SHOF. FI 1+2. MMM. FI 2. 1. FI 1. Mean SD Mean SD Mean SD. 15. .85 (1) [0.9] .87 (2) [0.8] .86 (3) [0.7] .88. .01 .01 .01 .01. .86 .90 .83 .85. .01 .01 .01 .01. .84 .83 .86 .89. .01 .01 .01 .01. .84 .86 .85 .86. .01 .01 .01 .01. .85 .88 .83 .84. .01 .01 .01 .01. .83 .82 .85 .87. .01 .01 .01 .01. .85 .87 .86 .88. .01 .01 .01 .01. .85 .87 .86 .88. .01 .01 .01 .01. .85 .86 .86 .88. .01 .01 .01 .01. .85 .86 .86 .86. .01 .01 .01 .01. .84 .86 .85 .86. .01 .01 .01 .01. .84 .86 .85 .86. .01 .01 .01 .01. 30. .87 (1) [0.9] .89 (2) [0.8] .90 (3) [0.7] .90. .01 .01 .01 .01. .87 .92 .87 .87. .01 .01 .01 .01. .86 .88 .90 .91. .01 .01 .01 .01. .86 .89 .88 .88. .01 .01 .01 .01. .86 .89 .87 .86. .01 .01 .01 .01. .86 .87 .88 .89. .01 .01 .01 .01. .87 .90 .90 .91. .01 .01 .01 .01. .87 .90 .90 .90. .01 .01 .01 .01. .87 .90 .89 .91. .01 .01 .01 .01. .86 .88 .88 .88. .01 .01 .01 .01. .86 .88 .88 .88. .01 .01 .01 .01. .86 .88 .88 .88. .01 .01 .01 .01. 60. .88 (1) [0.9] .92 (2) [0.8] .91 (3) [0.7] .92. .01 .01 .01 .01. .88 .93 .91 .90. .01 .01 .01 .01. .88 .91 .92 .92. .01 .01 .01 .01. .87 .90 .90 .90. .01 .01 .01 .01. .87 .90 .90 .89. .01 .01 .01 .01. .87 .90 .90 .90. .01 .01 .01 .01. .88 .92 .91 .92. .01 .01 .01 .01. .88 .92 .92 .92. .01 .01 .01 .01. .88 .92 .91 .92. .01 .01 .01 .01. .88 .90 .90 .90. .01 .01 .01 .01. .87 .91 .90 .90. .01 .01 .01 .01. .87 .90 .90 .90. .01 .01 .01 .01. 90. .88 (1) [0.9] .93 (2) [0.8] .93 (3) [0.7] .93. .01 .01 .01 .01. .88 .94 .93 .91. .01 .01 .01 .01. .89 .93 .93 .93. .01 .01 .01 .01. .88 .91 .91 .91. .01 .01 .01 .01. .88 .01 .91 .01 .91 .01 .90 .01 FI 2 = . .88 .90 .91 .91. .01 .01 .01 .01. .88 .93 .93 .93. .01 .01 .01 .01. .88 .92 .93 .93. .01 .01 .01 .01. .88 .93 .92 .93. .01 .88 .01 .91 .01 .91 .01 .91 FI 1 = . .01 .01 .01 .01. .88 .91 .91 .91. .01 .01 .01 .01. .88 .92 .91 .91. .01 .01 .01 .01. FI. 1+2 = . MTL = . SHOF = the Sympson and Hetter online procedure with Freeze MMM = the modified multinomial model. 60.
(77) 4-1-8. 1 SHOF. 1MTL1. FI 1+2. MMM. FI 2. FI 1. Mean SD Mean SD Mean SD. 1111. SHOF. 11111. FI 1+2. FI 2. FI 1. 111111 FI 1+2. MMM FI 2. 111111. 1. FI 1. SHOF FI 1+2. Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD. MMM. FI 2. 1 FI 1. Mean SD Mean SD Mean SD. 15. .82. .01. .88. .01. .79. .01. .83 .01 .89 .01 .82 .01. .81 .01 .81 .01 .81 .01. .83. .01. .83. .01. .83. .01. 30. .74. .01. .82. .01. .72. .01. .75 .01 .82 .01 .75 .01. .74 .01 .73 .01 .73 .01. .76. .01. .75. .01. .75. .01. 60. .65. .01. .69. .01. .65. .01. .69 .01 .71 .01 .68 .01. .65 .01 .66 .01 .66 .01. .69. .01. .69. .01. .69. .01. 90. .62. .01. .63. .01. .60. .01. .65 .01 .67 .01 .65 .01. .62 .01 .62 .01 .61 .01. .66. .01. .65. .01. .65. .01. FI 1+2 = . FI 2 = SHOF = the Sympson and Hetter online procedure with Freeze. MTL = . 4-1-9. 1 SHOF. 1MTL1. FI 1 = MMM = the modified multinomial model. FI 1+2. MMM. FI 2. FI 1. 11111 FI 1+2. SHOF. 111111. FI 2. FI 1. 111111 FI 1+2. Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD. MMM FI 2. 111111 FI 1. 1. SHOF FI 1+2. Mean SD Mean SD Mean SD. FI 2. MMM. 1 FI 1. Mean SD Mean SD Mean SD. 15. 13.44 0.09 13.89 0.09 13.17 0.08 13.71 0.06 14.14 0.08 13.65 0.08 13.51 0.06 13.50 0.08 13.50 0.09 13.71 0.08 13.76 0.08 13.77 0.08. 30. 24.91 0.23 26.73 0.28 24.35 0.26 25.60 0.22 26.95 0.21 25.52 0.21 25.05 0.20 24.97 0.25 25.04 0.26 25.73 0.21 25.66 0.27 25.62 0.22. 60. 45.32 0.50 48.93 0.42 44.72 0.51 47.52 0.45 49.90 0.43 47.16 0.51 45.73 0.65 46.00 0.45 45.62 0.43 47.43 0.49 47.49 0.41 47.55 0.42. 90. 64.73 0.81 68.57 0.74 63.15 0.90 67.87 0.58 71.13 0.88 67.56 0.88 64.79 0.94 64.94 0.71 64.63 0.77 68.24 0.68 68.07 0.65 68.02 0.67 FI 1+2 = MTL = . FI 2 = SHOF = the Sympson and Hetter online procedure with Freeze. 61. FI 1 = MMM = the modified multinomial model.
(78) 4-1-10. 1 SHOF. 1MTL1. FI 1+2. MMM. FI 2. 11111. FI 1. FI 1+2. Mean SD Mean SD Mean SD. SHOF. 111111. FI 2. FI 1. 111111 FI 1+2. Mean SD Mean SD Mean SD. MMM FI 2. 111111. 1. FI 1. Mean SD Mean SD Mean SD. SHOF FI 1+2. MMM. FI 2. 1 FI 1. Mean SD Mean SD Mean SD. 15. 1.00 .00 1.00 .00 1.00 .00. .20. .00 .20. .00. .20. .00. .87. .01. .87. .01. .87 .01. .20. .00. .20. .00. .20. .00. 30. 1.00 .00 1.00 .00 1.00 .00. .20. .00 .20. .00. .20. .00. .88. .01. .88. .01. .88 .01. .20. .00. .20. .00. .20. .00. 60. 1.00 .00 1.00 .00 1.00 .00. .20. .00 .20. .00. .20. .00. .89. .01. .89. .01. .89 .01. .20. .00. .20. .00. .20. .00. 90. 1.00 .00 1.00 .00 1.00 .00. .20. .00 .20. .00. .20. .00. .89. .01. .90. .01. .89 .01. .20. .00. .20. .00. .20. .00. FI 1+2 = . FI 2 = SHOF = the Sympson and Hetter online procedure with Freeze. MTL = . 4-1-11. 1 SHOF. 1MTL1. FI 1 = MMM = the modified multinomial model. FI 1+2. MMM. FI 2. 11111. FI 1. FI 1+2. Mean SD Mean SD Mean SD. SHOF. 111111. FI 2. FI 1. Mean SD Mean SD Mean SD. 111111 FI 1+2. MMM FI 2. 111111 FI 1. Mean SD Mean SD Mean SD. 1. SHOF FI 1+2. MMM. FI 2. 1 FI 1. Mean SD Mean SD Mean SD. 15. .07. .00. .08. .00. .07. .00. .12. .00. .13. .00. .12 .00. .07. .00. .08 .00. .07 .00. .13 .00. .13. .00. .13. .00. 30. .14. .00. .13. .00. .14. .00. .23. .00. .25. .00. .23 .00. .15. .00. .14 .00. .14 .00. .23 .00. .23. .00. .23. .00. 60. .26. .01. .23. .01. .25. .00. .41. .01. .43. .00. .41 .00. .26. .01. .25 .01. .25 .01. .42 .01. .42. .01. .42. .01. 90. .34. .01. .31. .01. .34. .01. .54. .01. .58. .01. .56 .01. .34. .01. .34 .01. .34 .01. .55 .01. .55. .01. .55. .01. FI 1+2 = MTL = . FI 2 = SHOF = the Sympson and Hetter online procedure with Freeze. 62. FI 1 = MMM = the modified multinomial model.
(79) 4-1-12. 1 SHOF. MTL. [. 15. 30. 60. 90. FI. ]. FI 1+2. FI 2. MMM FI 1. 11111 FI 1+2. SHOF FI 2. 11111 FI 1. 111111 FI 1+2. MMM FI 2. 11111 1 FI 1. SHOF FI 1+2. FI 2. MMM. 1 FI 1. Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD. A [0.9]. .33 .00 .72 .00 .16 .00. .34 .00 .62 .00 .15 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. B [0.8]. .31 .00 .17 .00 .34 .00. .32 .00 .23 .00 .35 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. C [0.7]. .36 .00 .11 .00 .50 .00. .34 .00 .14 .00 .49 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. A [0.9]. .34 .00 .67 .00 .22 .00. .33 .00 .52 .00 .21 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. B [0.8]. .33 .00 .21 .00 .36 .00. .33 .00 .33 .00 .36 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. C [0.7]. .33 .00 .12 .00 .42 .00. .34 .00 .16 .00 .43 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. A [0.9]. .33 .00 .56 .00 .27 .00. .33 .00 .46 .00 .24 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. B [0.8]. .34 .00 .29 .00 .36 .00. .34 .00 .34 .00 .36 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. C [0.7]. .33 .00 .15 .00 .38 .00. .34 .00 .20 .00 .40 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. A [0.9]. .33 .00 .54 .00 .28 .00. .33 .00 .41 .00 .25 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. B [0.8]. .34 .00 .30 .00 .35 .00. .34 .00 .36 .00 .36 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. C [0.7]. .33 .00 .16 .00 .37 .00. .33 .00 .23 .00 .38 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. 1+2 =. MTL = . FI 2 = SHOF = the Sympson and Hetter online procedure with Freeze. 63. FI 1 = MMM = the modified multinomial model.
(80) 1. 4-1-13. 1 SHOF. FI. = 15. 2%. 90 .88. SHOF MMM. FI. FI1+2 SHOF. MMM MMM. MMM SHOF. MMM. FI FI1+2. MMM. SHOF. SHOF. MMM 1% 4-1-14. SHOF. FI 4%. MMM. FI. FI1+2 SHOF. MMM. MMM. 1%. MMM SHOF. MMM. FI. MMM FI1+2. 64. SHOF. MMM.
(81) SHOF. MMM. 3. 15 30 60 .86. 90. .95. 2. 4-1-15. 1 SHOF = 90. MMM. FI 3.71. FI. FI1+2. MMM. SHOF. MMM. 0.31. MMM. SHOF. MMM. FI. MMM. FI1+2 SHOF. MMM. SHOF = 90. 2.97. 3. 4-1-16. 1 SHOF .2 .80. MMM. .82. 65. MMM.
(82) 4. 4-1-17. 1 SHOF = 90. 14%. MMM. FI. FI1+2. MMM. SHOF. MMM. 1%. MMM. SHOF. MMM. FI FI1+2. SHOF. MMM. SHOF. MMM. = 90. 11% 5. 4-1-18. 1 MMM 1/3. FI2. SHOF [0.9]. FI1. [0.7]. FI2. 6. 1. SHOF. MMM SHOF. MMM. FI 66.
(83) 4-1-13. 1 SHOF. FI 1+2. MTL [. ]. MMM. FI 2. 11111. FI 1. SHOF. FI 1+2. FI 2. 11111 11111. FI 1. MMM. FI 1+2. FI 2. 11111. FI 1. Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD. .83 .55 .60 .61. .01 .02 .02 .02. .84 .64 .49 .52. .01 .01 .02 .01. .84 .70 .43 .39. .01 .01 .01 .01. .83 .55 .57 .64. .01 .02 .02 .02. .85 .61 .50 .50. .01 .01 .02 .01. .85 .60 .49 .50. .01 .02 .01 .02. .86 .01 .86 .01 .85 .01 .87 .01 .87 .01 .87 .01 .57 .01 .62 .01 .49 .02 .54 .01 .55 .01 .55 .01 .42 .01 .40 .01 .50 .01 .43 .02 .43 .01 .42 .02. .87 .01 .86 .01 .86 .01 .54 .01 .54 .02 .54 .02 .46 .02 .46 .01 .46 .02. (3) [0.7] .41 .02 .27 .01 .52 .02. .46 .01 .32 .01 .56 .02 .43 .02 .43 .01 .43 .02. .46 .01 .46 .02 .46 .02. 60. .88 (1) [0.9] .54 (2) [0.8] .30 (3) [0.7] .36. .01 .01 .02 .01. .88 .58 .29 .23. .01 .01 .01 .01. .88 .45 .49 .48. .01 .02 .01 .01. .87 .53 .40 .42. .01 .01 .01 .01. .88 .56 .38 .30. .01 .02 .02 .01. .87 .45 .46 .51. .01 .01 .02 .01. .88 .50 .38 .39. .01 .01 .02 .02. .88 .49 .38 .39. .01 .01 .02 .02. .88 .50 .38 .39. .01 .01 .01 .02. .87 .50 .42 .41. .01 .01 .02 .01. .87 .50 .42 .41. .01 .01 .02 .01. .87 .50 .42 .42. .01 .01 .02 .02. 90. .88 (1) [0.9] .52 (2) [0.8] .29 (3) [0.7] .35. .01 .02 .02 .01. .88 .56 .28 .21. .01 .01 .01 .01. .88 .44 .47 .46. .01 .01 .01 .02. .88 .51 .38 .41. .01 .02 .01 .01. .88 .54 .37 .30. .01 .02 .02 .01. .88 .43 .45 .49. .01 .02 .01 .01. .88 .48 .36 .37. .01 .02 .01 .01. .89 .48 .37 .37. .01 .01 .02 .01. .88 .48 .37 .37. .01 .02 .01 .02. .88 .48 .41 .40. .01 .01 .01 .01. .88 .48 .40 .40. .01 .01 .01 .01. .88 .49 .40 .40. .01 .02 .02 .02. 67. .01 .01 .02 .01. Mean SD Mean SD Mean SD. .87 .01 .87 .01 .86 .01 (1) [0.9] .57 .01 .63 .02 .49 .02 (2) [0.8] .33 .01 .32 .01 .53 .01. FI 2 = SHOF = the Sympson and Hetter online procedure with Freeze. .85 .61 .49 .50. FI 1. 30. MTL = . .01 .01 .02 .01. FI 2. 1. .85 (1) [0.9] .64 (2) [0.8] .40 (3) [0.7] .47. 1+2 =. .86 .70 .37 .36. FI 1+2. MMM. 15. FI. .01 .01 .02 .02. SHOF. .84 .61 .53 .52. .02 .02 .01 .01. .84 .61 .52 .52. .01 .01 .01 .01. .84 .62 .53 .53. .01 .02 .02 .02. FI 1 = MMM = the modified multinomial model.
(84) 4-1-14. 1 SHOF. 1MTL1. FI 1+2. MMM. FI 2. 11111. FI 1. FI 1+2. Mean SD Mean SD Mean SD. SHOF. 111111. FI 2. FI 1. 111111 FI 1+2. MMM. 111111. FI 2. 1. FI 1. SHOF FI 1+2. Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD. MMM. FI 2. 1 FI 1. Mean SD Mean SD Mean SD. 15. .47. .01. .45. .01. .49. .02. .51 .01 .48 .01 .53 .02. .47 .01 .47 .01 .47 .02. .50. .01. .50. .01. .51. .01. 30. .33. .01. .32. .01. .33. .01. .36 .02 .35 .01 .37 .02. .34 .01 .33 .01 .34 .01. .36. .01. .36. .01. .36. .02. 60. .24. .01. .24. .01. .24. .01. .28 .01 .26 .01 .27 .01. .24 .02 .24 .02 .24 .01. .27. .01. .27. .01. .27. .01. 90. .21. .01. .20. .01. .20. .01. .23 .01 .22 .01 .23 .01. .21 .01 .20 .01 .20 .01. .23. .01. .23. .01. .23. .01. FI. 1+2 =. FI 2 = SHOF = the Sympson and Hetter online procedure with Freeze. MTL = . 4-1-15. 1 SHOF. 1MTL1. FI 1 = MMM = the modified multinomial model. FI 1+2. FI 2. MMM FI 1. 11111 FI 1+2. SHOF. 111111. FI 2. FI 1. 111111 FI 1+2. Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD. MMM. 111111. FI 2. FI 1. Mean SD Mean SD Mean SD. 1. SHOF FI 1+2. FI 2. MMM. 1 FI 1. Mean SD Mean SD Mean SD. 15. 9.95 0.16 9.68 0.11 10.82 0.12 10.62 0.13 10.29 0.12 11.23 0.13 10.30 0.13 10.24 0.10 10.23 0.14 10.69 0.12 10.74 0.10 10.79 0.12. 30. 15.66 0.26 15.40 0.21 16.77 0.18 16.90 0.40 16.55 0.29 17.89 0.31 16.20 0.26 16.19 0.27 16.29 0.28 17.17 0.25 17.16 0.25 17.12 0.27. 60. 24.09 0.59 23.52 0.62 25.80 0.65 26.66 0.56 25.83 0.64 27.51 0.68 24.42 0.57 24.64 0.45 24.46 0.45 26.71 0.43 26.44 0.47 26.68 0.49. 90. 31.14 0.94 29.73 0.92 31.61 0.81 34.16 1.02 33.44 0.81 35.17 0.94 31.45 0.81 31.25 0.67 31.02 0.85 34.11 1.05 34.27 0.82 34.17 0.82. FI. 1+2 =. MTL = . FI 2 = SHOF = the Sympson and Hetter online procedure with Freeze. 68. FI 1 = MMM = the modified multinomial model.
(85) 4-1-16. 1 SHOF. 1MTL1. FI 1+2. MMM. FI 2. 11111. FI 1. FI 1+2. Mean SD Mean SD Mean SD. SHOF. 111111. FI 2. FI 1. Mean SD Mean SD Mean SD. 111111 FI 1+2. MMM FI 2. 111111. 1. FI 1. SHOF FI 1+2. Mean SD Mean SD Mean SD. MMM. FI 2. 1 FI 1. Mean SD Mean SD Mean SD. 15. 1.00 .00 1.00 .00 1.00 .00. .20. .00. .20. .00. .20 .00. .81. .01. .80 .01. .80. .01. .20 .00. .20. .00. .20. .00. 30. 1.00 .00 1.00 .00 1.00 .00. .20. .00. .20. .00. .20 .00. .81. .01. .81 .01. .81. .01. .20 .00. .20. .00. .20. .00. 60. 1.00 .00 1.00 .00 1.00 .00. .20. .00. .20. .00. .20 .00. .81. .01. .81 .01. .82. .01. .20 .00. .20. .00. .20. .00. 90. 1.00 .00 1.00 .00 1.00 .00. .20. .00. .20. .00. .20 .00. .82. .01. .82 .01. .81. .01. .20 .00. .20. .00. .20. .00. FI. 1+2 =. FI 2 = SHOF = the Sympson and Hetter online procedure with Freeze. MTL = . 4-1-17. 1 SHOF. 1MTL1. FI 1 = MMM = the modified multinomial model. FI 1+2. MMM. FI 2. 11111. FI 1. FI 1+2. Mean SD Mean SD Mean SD. SHOF. 111111. FI 2. FI 1. 111111 FI 1+2. Mean SD Mean SD Mean SD. MMM FI 2. 111111 FI 1. Mean SD Mean SD Mean SD. 1. SHOF FI 1+2. MMM. FI 2. 1 FI 1. Mean SD Mean SD Mean SD. 15. .06. .00. .05. .00. .05. .00. .10. .00 .10. .00. .10. .00. .06. .00. .06. .00. .06 .00. .10. .00. .10. .00. .10. .00. 30. .10. .00. .09. .00. .11. .00. .16. .00 .17. .00. .17. .00. .11. .00. .10. .00. .11 .00. .16. .00. .16. .00. .16. .00. 60. .19. .01. .17. .00. .18. .01. .28. .00 .28. .00. .27. .00. .19. .00. .19. .00. .18 .01. .28. .01. .28. .00. .28. .00. 90. .26. .01. .23. .01. .25. .01. .36. .00 .37. .00. .36. .01. .26. .00. .26. .01. .26 .01. .37. .01. .37. .00. .37. .00. FI 1+2 =. FI 2 = MTL = . FI 1 =. SHOF = the Sympson and Hetter online procedure with Freeze. 69. MMM = the modified multinomial model.
(86) 4-1-18. 1 SHOF. MTL. 15. 30. 60. 90. [. ]. FI 1+2. FI 2. MMM FI 1. 11111 FI 1+2. SHOF FI 2. 11111 FI 1. 111111 FI 1+2. MMM FI 2. 11111 1 FI 1. SHOF FI 1+2. FI 2. MMM. 1 FI 1. Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD. A [0.9]. .34 .00 .74 .00 .14 .00. .35 .00 .66 .00 .14 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. B [0.8]. .31 .00 .14 .00 .34 .00. .31 .00 .20 .00 .34 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. C [0.7]. .35 .00 .12 .00 .52 .00. .34 .00 .14 .00 .52 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. A [0.9]. .35 .00 .69 .00 .20 .00. .34 .00 .56 .00 .19 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. B [0.8]. .33 .00 .18 .00 .36 .00. .32 .00 .29 .00 .35 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. C [0.7]. .33 .00 .13 .00 .44 .00. .33 .00 .15 .00 .46 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. A [0.9]. .34 .00 .61 .00 .24 .00. .34 .00 .50 .00 .23 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. B [0.8]. .34 .00 .26 .00 .36 .00. .33 .00 .32 .00 .35 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. C [0.7]. .32 .00 .14 .00 .40 .00. .33 .00 .18 .00 .42 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. A [0.9]. .34 .00 .58 .00 .26 .00. .33 .00 .48 .00 .24 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. B [0.8]. .34 .00 .27 .00 .35 .00. .33 .00 .44 .00 .35 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. C [0.7]. .32 .00 .15 .00 .39 .00. .33 .00 .20 .00 .41 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. FI 1+2 =. FI 2 = MTL = . FI 1 =. SHOF = the Sympson and Hetter online procedure with Freeze. 70. MMM = the modified multinomial model.
(87) 1. 4-1-19. 1 SHOF. FI. 3 4%. MMM. FI. FI1+2 SHOF. MMM. MMM. 1%. MMM SHOF. MMM. FI. MMM FI1+2. SHOF. MMM. SHOF. MMM. 3 2% 4-1-20. SHOF. FI 5%. MMM. FI. FI1+2 SHOF. MMM. MMM. 1%. MMM. SHOF. MMM. FI. MMM FI1+2 SHOF. SHOF. MMM. 4% 71. MMM.
(88) 15 30 60 .98. 90. 1.00. 2. 4-1-21. 1 SHOF = 90. MMM. FI 4.46. FI. FI1+2. MMM. SHOF. MMM. 0.57. MMM. SHOF. MMM. FI. MMM. FI1+2 SHOF. MMM. SHOF = 90. MMM. 3.83. 3. 4-1-22. 1 SHOF .2 .87. MMM. .90. 4. 4-1-23. 1 SHOF = 90. 26% 72. MMM.
(89) FI. FI1+2. MMM. SHOF. MMM. 1% SHOF. MMM MMM. FI. FI1+2. SHOF. MMM. SHOF = 90. MMM 20. 5. 4-1-24. 1 MMM 1/3. SHOF. FI2. [0.9]. FI1. [0.7]. FI2. 6. 1 SHOF. MMM SHOF. MMM. FI. 73.
(90) 4-1-19. 1 SHOF. FI 1+2. MTL [. ]. MMM. FI 2. 11111. FI 1. SHOF. FI 1+2. FI 2. 11111 11111. FI 1. MMM. FI 1+2. FI 2. 11111. FI 1. SHOF. FI 1+2. Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD. MMM. FI 2. 1. FI 1. Mean SD Mean SD Mean SD. 15. .86 (1) [0.9] .87 (2) [0.8] .86 (3) [0.7] .88. .01 .01 .01 .01. .86 .89 .82 .84. .01 .01 .01 .01. .84 .83 .86 .89. .01 .01 .01 .01. .84 .86 .85 .86. .01 .01 .01 .01. .85 .87 .82 .83. .01 .01 .01 .01. .83 .83 .85 .87. .01 .01 .01 .01. .85 .87 .87 .88. .01 .01 .01 .01. .85 .87 .86 .88. .01 .01 .01 .01. .85 .87 .86 .88. .01 .01 .01 .01. .84 .86 .85 .86. .01 .01 .01 .01. .84 .85 .85 .86. .01 .01 .01 .01. .84 .86 .85 .85. .01 .01 .01 .01. 30. .87 (1) [0.9] .90 (2) [0.8] .89 (3) [0.7] .90. .01 .01 .01 .01. .87 .91 .87 .88. .01 .01 .01 .01. .87 .88 .90 .90. .01 .01 .01 .01. .86 .89 .88 .88. .01 .01 .01 .01. .86 .89 .87 .86. .01 .01 .01 .01. .86 .87 .88 .89. .01 .01 .01 .01. .87 .90 .89 .90. .01 .01 .01 .01. .87 .89 .89 .90. .01 .01 .01 .01. .87 .89 .89 .90. .01 .01 .01 .01. .86 .88 .88 .88. .01 .01 .01 .01. .86 .89 .88 .88. .01 .01 .01 .01. .86 .89 .88 .88. .01 .01 .01 .01. 60. .88 (1) [0.9] .92 (2) [0.8] .91 (3) [0.7] .92. .01 .01 .01 .01. .88 .93 .91 .90. .01 .01 .01 .01. .87 .91 .92 .92. .01 .01 .01 .01. .87 .90 .89 .90. .01 .01 .01 .01. .87 .90 .90 .88. .01 .01 .01 .01. .87 .90 .91 .90. .01 .01 .01 .01. .88 .92 .92 .92. .01 .01 .01 .01. .88 .92 .92 .92. .01 .01 .01 .01. .88 .92 .92 .92. .01 .01 .01 .01. .87 .90 .90 .90. .01 .01 .01 .01. .88 .91 .90 .90. .01 .01 .01 .01. .87 .91 .90 .90. .01 .01 .01 .01. 90. .88 (1) [0.9] .93 (2) [0.8] .93 (3) [0.7] .93. .01 .01 .01 .01. .88 .94 .92 .92. .01 .01 .01 .01. .88 .92 .93 .93. .01 .01 .01 .01. .88 .91 .91 .91. .01 .01 .01 .01. .87 .90 .91 .90. .01 .01 .01 .01. .87 .91 .91 .91. .01 .01 .01 .01. .88 .93 .93 .93. .01 .01 .01 .01. .88 .93 .93 .93. .01 .01 .01 .01. .88 .93 .93 .93. .01 .01 .01 .01. .87 .91 .91 .91. .01 .01 .01 .01. .87 .91 .91 .91. .01 .01 .01 .01. .87 .91 .91 .90. .01 .01 .01 .01. FI. FI 2 = . 1+2 = . MTL = . FI 1 = . SHOF = the Sympson and Hetter online procedure with Freeze MMM = the modified multinomial model. 74.
(91) 4-1-20. 1 SHOF. 1MTL1. FI 1+2. MMM. FI 2. 11111. FI 1. FI 1+2. Mean SD Mean SD Mean SD. SHOF. 111111. FI 2. FI 1. 111111 FI 1+2. MMM FI 2. 111111. 1. FI 1. Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD. SHOF FI 1+2. MMM. FI 2. 1 FI 1. Mean SD Mean SD Mean SD. 15. .82. .01. .89. .01. .79. .01. .83 .01 .89 .01 .82 .01. .81 .01 .81 .01 .81 .01. .83. .01. .83. .01. .83. .01. 30. .73. .01. .82. .01. .72. .01. .75 .01 .82 .01 .75 .01. .73 .01 .74 .01 .73 .01. .75. .01. .75. .01. .76. .01. 60. .66. .01. .69. .01. .64. .01. .69 .01 .72 .01 .68 .01. .65 .01 .65 .01 .65 .01. .69. .01. .69. .01. .69. .01. 90. .61. .01. .62. .01. .60. .01. .65 .01 .67 .01 .65 .01. .61 .01 .61 .01 .61 .01. .65. .01. .65. .01. .65. .01. FI. FI 2 = . 1+2 = . MTL = . 4-1-21. SHOF = the Sympson and Hetter online procedure with Freeze MMM = the modified multinomial model. 1 SHOF. 1MTL1. FI 1 = . FI 1+2. MMM. FI 2. FI 1. 11111 FI 1+2. SHOF. 111111. FI 2. FI 1. 111111 FI 1+2. Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD. MMM FI 2. 111111 FI 1. Mean SD Mean SD Mean SD. 1. SHOF FI 1+2. FI 2. MMM. 1 FI 1. Mean SD Mean SD Mean SD. 15. 13.48 0.09 13.93 0.07 13.12 0.08 13.74 0.07 14.12 0.09 13.63 0.08 13.49 0.07 13.52 0.11 13.50 0.08 13.76 0.06 13.75 0.08 13.77 0.09. 30. 24.79 0.22 26.73 0.16 24.50 0.25 25.59 0.22 26.90 0.17 25.43 0.24 24.96 0.24 25.10 0.22 25.01 0.19 25.62 0.22 25.68 0.20 25.74 0.23. 60. 45.63 0.46 48.91 0.36 44.47 0.55 47.36 0.61 49.92 0.36 47.12 0.46 45.70 0.50 45.54 0.46 45.74 0.35 47.61 0.55 47.44 0.51 47.46 0.52. 90. 64.28 0.94 68.27 0.53 63.14 0.88 68.26 0.96 71.03 0.82 67.60 1.11 64.85 0.64 64.56 0.84 64.54 0.81 68.11 1.05 68.01 0.90 68.22 0.79. FI. FI 2 = . 1+2 = . MTL = . FI 1 = . SHOF = the Sympson and Hetter online procedure with Freeze MMM = the modified multinomial model. 75.
(92) 4-1-22. 1 SHOF. 1MTL1. FI 1+2. MMM. FI 2. 11111. FI 1. FI 1+2. Mean SD Mean SD Mean SD. SHOF. 111111. FI 2. FI 1. 111111 FI 1+2. Mean SD Mean SD Mean SD. MMM FI 2. 111111. 1. FI 1. Mean SD Mean SD Mean SD. SHOF FI 1+2. MMM. FI 2. 1 FI 1. Mean SD Mean SD Mean SD. 15. 1.00 .00 1.00 .00 1.00 .00. .20. .00 .20. .00. .20. .00. .87. .01. .87. .01. .87 .01. .20. .00. .20. .00. .20. .00. 30. 1.00 .00 1.00 .00 1.00 .00. .20. .00 .20. .00. .20. .00. .88. .01. .88. .01. .88 .01. .20. .00. .20. .00. .20. .00. 60. 1.00 .00 1.00 .00 1.00 .00. .20. .00 .20. .00. .20. .00. .89. .01. .89. .01. .89 .01. .20. .00. .20. .00. .20. .00. 90. 1.00 .00 1.00 .00 1.00 .00. .20. .00 .20. .00. .20. .00. .89. .01. .90. .01. .89 .01. .20. .00. .20. .00. .20. .00. FI. FI 2 = . 1+2 = . MTL = . 4-1-23. SHOF = the Sympson and Hetter online procedure with Freeze MMM = the modified multinomial model. 1 SHOF. 1MTL1. FI 1 = . FI 1+2. MMM. FI 2. 11111. FI 1. FI 1+2. Mean SD Mean SD Mean SD. SHOF. 111111. FI 2. FI 1. Mean SD Mean SD Mean SD. 111111 FI 1+2. MMM FI 2. 111111 FI 1. Mean SD Mean SD Mean SD. 1. SHOF FI 1+2. MMM. FI 2. 1 FI 1. Mean SD Mean SD Mean SD. 15. .07. .00. .08. .00. .07. .00. .12. .00. .13. .00. .12 .00. .07. .00. .08 .00. .07 .00. .13 .00. .13. .00. .13. .00. 30. .14. .00. .13. .00. .14. .00. .23. .00. .25. .00. .23 .00. .14. .00. .15 .00. .15 .00. .23 .00. .23. .00. .23. .00. 60. .26. .01. .22. .00. .25. .00. .41. .00. .43. .00. .41 .00. .26. .01. .25 .01. .25 .01. .42 .01. .42. .01. .42. .01. 90. .35. .01. .31. .00. .33. .00. .55. .00. .57. .01. .55 .00. .35. .01. .34 .01. .34 .00. .55 .01. .55. .01. .55. .01. FI. FI 2 = . 1+2 = . MTL = . FI 1 = . SHOF = the Sympson and Hetter online procedure with Freeze MMM = the modified multinomial model. 76.
(93) 4-1-24. 1 SHOF. MTL. [. 15. 30. 60. 90. FI. ]. FI 1+2. FI 2. MMM FI 1. 11111 FI 1+2. SHOF FI 2. 11111 FI 1. 111111 FI 1+2. MMM FI 2. 11111 1 FI 1. SHOF FI 1+2. FI 2. MMM. 1 FI 1. Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD. A [0.9]. .33 .00 .72 .00 .16 .00. .34 .00 .63 .00 .15 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. B [0.8]. .31 .00 .17 .00 .34 .00. .32 .00 .23 .00 .35 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. C [0.7]. .36 .00 .11 .00 .50 .00. .35 .00 .14 .00 .49 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. A [0.9]. .34 .00 .67 .00 .22 .00. .33 .00 .51 .00 .21 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. B [0.8]. .33 .00 .21 .00 .36 .00. .33 .00 .33 .00 .36 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. C [0.7]. .33 .00 .12 .00 .41 .00. .34 .00 .16 .00 .43 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. A [0.9]. .33 .00 .57 .00 .27 .00. .33 .00 .46 .00 .24 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. B [0.8]. .34 .00 .29 .00 .36 .00. .34 .00 .34 .00 .36 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. C [0.7]. .33 .00 .15 .00 .38 .00. .34 .00 .20 .00 .40 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. A [0.9]. .33 .00 .54 .00 .28 .00. .33 .00 .41 .00 .25 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. B [0.8]. .34 .00 .30 .00 .35 .00. .34 .00 .36 .00 .36 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. C [0.7]. .33 .00 .16 .00 .37 .00. .33 .00 .23 .00 .38 .00 .33 .00 .33 .00 .33 .00. .33 .00 .33 .00 .33 .00. FI 2 = . 1+2 = . MTL = . FI 1 = . SHOF = the Sympson and Hetter online procedure with Freeze MMM = the modified multinomial model. 77.
(94) 2. 4-2-1 70%. = 30 .75 .85. .76. FI. 3. .73. 120 .85. .78 3. .89 70% = 30 .74. FI. .76. .78. 120 3. 70%. = 30 .85. FI 120. 78. .73 .85. .89.
(95) 2. 1%. 2.25. 3. FI. 2. 1. FI2. FI1. [0.7]. [0.8] [0.9]. 2. 4-2-2. = 30 .67. .74. 1. FI 120. .37. .38. = 30 .94. .96. 120. .88. .90. FI FI1 FI FI2. FI1 79. FI1+2.
(96) 30 .98. .86. 60. 90. 120. 1.00. .93 .99. 2. 4-2-3. 1.00. 1 FI = 30. 25.52. 26.33. 120. 66.44. 69.05. = 30 29.33. 29.51. 112.12. FI1. 120. 111.10. FI. FI FI2. FI1+2. 80. FI1.
(97) 2. 4-2-4. 1. FI 1. 2. 4-2-5. = 30. 1. FI. 120. .11 .34. .39. = 30 120. .43. FI1. .47. .15. .16. FI. FI1+2. 2. .13. FI1. 4-2-6. FI1+2. FI2. 1 FI. FI1+2. 1/3 81. FI2.
(98) [0.9]. FI1. [0.7]. 2 = 30 70%. FI FI2. FI1. [0.7]. [0.8]. [0.9]. FI. FI1 FI FI2. FI1 FI1+2 FI2. FI1. [0.9] [0.7]. 82. FI1+2.
(99) 4-2-1. 2 FI 1+2. MTL. [. ]. FI 1. FI 1+2. FI 2. FI 1. FI 1+2. FI 2. FI 1. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. (1) [0.9] (2) [0.8] (3) [0.7]. .75 .81 .80 .81. .01 .01 .01 .01. .76 .85 .76 .73. .01 .01 .01 .01. .75 .78 .80 .82. .01 .02 .01 .01. .75 .58 .58 .59. .01 .02 .02 .01. .76 .62 .50 .46. .01 .01 .01 .01. .74 .56 .61 .65. .01 .01 .01 .01. .75 .81 .79 .81. .01 .01 .01 .01. .75 .85 .76 .73. .02 .01 .02 .01. .74 .78 .80 .82. .01 .01 .01 .01. (1) [0.9]. .77 .85. .01 .01. .77 .87. .01 .01. .77 .84. .01 .01. .77 .46. .01 .02. .77 .50. .01 .02. .76 .43. .01 .02. .77 .85. .01 .01. .77 .88. .01 .02. .77 .83. .02 .01. (2) [0.8]. .84. .01. .83. .01. .85. .01. .45. .02. .42. .02. .47. .01. .84. .01. .83. .01. .84. .01. (3) [0.7]. .84. .01. .81. .01. .84. .01. .46. .01. .38. .01. .51. .02. .85. .01. .80. .01. .85. .01. (1) [0.9] (2) [0.8] (3) [0.7]. .77 .86 .86 .86. .01 .01 .01 .01. .78 .88 .86 .84. .01 .01 .01 .01. .78 .86 .86 .86. .02 .01 .01 .01. .77 .41 .41 .42. .01 .02 .02 .02. .77 .46 .39 .35. .01 .02 .01 .01. .77 .38 .43 .46. .02 .02 .01 .01. .77 .87 .86 .86. .01 .01 .01 .01. .77 .88 .86 .83. .01 .01 .01 .01. .77 .86 .86 .87. .01 .02 .01 .01. (1) [0.9] (2) [0.8] (3) [0.7]. .78 .87 .88 .87. .01 .01 .01 .01. .78 .89 .88 .85. .01 .01 .01 .01. .78 .87 .87 .87. .01 .01 .01 .01. .78 .38 .38 .39. .01 .02 .01 .02. .78 .43 .36 .33. .01 .02 .01 .01. .78 .36 .40 .44. .01 .01 .02 .02. .78 .88 .87 .88. .01 .01 .00 .01. .78 .89 .87 .85. .01 .01 .01 .01. .78 .87 .88 .88. .01 .01 .01 .01. 30. 60. 90. 120. FI. FI 2. FI 2 = . 1+2 = . MTL = . 83. FI 1 = .
(100) 4-2-2 MTL. 2 FI 1+2. FI 2. FI 1. FI 1+2. FI 2. FI 1. FI 1+2. FI 1. Mean. SD. Mean. SD. Mean. SD. 30. .95. .00. .96. .00. .94. .01. .72. .02. .67. .01. .74. .01. .95. .00. .96. .01. .94. .01. 60. .92. .00. .92. .01. .92. .01. .50. .02. .48. .01. .50. .02. .92. .01. .92. .01. .92. .01. 90. .91. .00. .91. .00. .90. .01. .42. .02. .41. .02. .41. .01. .91. .01. .90. .01. .90. .01. 120. .89. .01. .90. .01. .88. .01. .38. .02. .37. .01. .37. .01. .89. .01. .88. .01. .88. .01. FI. Mean SD Mean SD Mean SD. FI 2. Mean SD Mean SD Mean SD. FI 2 = . 1+2 = . FI 1 = . MTL = . 4-2-3. MTL. 2. FI 1+2. FI 2. FI 1. FI 1+2. FI 2. FI 1. FI 1+2. FI 2. FI 1. Mean. SD. Mean. SD. Mean. SD. Mean SD Mean SD Mean SD. Mean SD Mean SD Mean SD. 30. 29.38. 0.06. 29.51. 0.05. 29.33. 0.11. 25.85 0.26 25.52 0.24 26.33 0.19. 29.36 0.10 29.50 0.09 29.34 0.08. 60. 57.30. 0.26. 57.57. 0.27. 57.23. 0.27. 43.32 0.54 42.15 0.49 43.88 0.44. 57.38 0.22 57.60 0.24 57.24 0.27. 90. 84.75. 0.37. 85.06. 0.30. 84.30. 0.52. 57.19 0.96 55.24 1.32 57.22 1.04. 84.67 0.52 84.84 0.47 84.63 0.45. 120. 111.85. 0.53. 112.11. 0.62. 111.35. 0.71. 68.66 1.47 66.44 1.20 69.05 0.94 111.93 0.60 112.12 0.61 111.10 0.53. FI 1+2 = . FI 2 = . FI 1 = . MTL = . 84.
(101) 4-2-4. 2. MTL. FI 1+2. FI 2. FI 1. FI 1+2. FI 2. FI 1. FI 1+2. FI 1. Mean. SD. Mean. SD. Mean. SD. 30. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 60. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 90. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 120. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. 1.00. .00. FI. Mean SD Mean SD Mean SD. FI 2. Mean SD Mean SD Mean SD. FI 2 = . 1+2 = . FI 1 = . MTL = . 4-2-5 MTL. 2 FI 1+2. FI 2. FI 1. FI 1+2. FI 2. FI 1. FI 1+2. FI 2. FI 1. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. 30. .16. .00. .15. .00. .15. .00. .13. .00. .11. .00. .13. .00. .15. .00. .15. .00. .15. .00. 60. .27. .01. .26. .01. .27. .01. .22. .00. .19. .00. .22. .00. .27. .00. .26. .01. .26. .00. 90. .38. .01. .35. .01. .36. .01. .31. .00. .27. .00. .30. .01. .37. .01. .35. .01. .36. .01. 120. .47. .01. .44. .01. .45. .01. .39. .01. .34. .00. .38. .01. .47. .01. .43. .01. .45. .01. FI. FI 2 = . 1+2 = . MTL = . 85. FI 1 = . Mean SD.
(102) 4-2-6 MTL. 2. [. 30. 60. 90. 120. FI. ]. FI 1+2. FI 2. FI 1. FI 1+2. FI 2. FI 1. FI 1+2. FI 2. FI 1. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. Mean. SD. A [0.9]. .34. .00. .65. .00. .23. .00. .34. .00. .68. .00. .23. .00. .34. .00. .65. .00. .23. .00. B [0.8]. .33. .00. .22. .00. .36. .00. .33. .00. .20. .00. .36. .00. .33. .00. .22. .00. .36. .00. C [0.7]. .33. .00. .12. .00. .41. .00. .33. .00. .11. .00. .41. .00. .33. .00. .12. .00. .41. .00. A [0.9]. .33. .00. .55. .00. .27. .00. .34. .00. .59. .00. .27. .00. .33. .00. .55. .00. .27. .00. B [0.8]. .34. .00. .30. .00. .35. .00. .34. .00. .27. .00. .35. .00. .34. .00. .30. .00. .35. .00. C [0.7]. .33. .00. .15. .00. .37. .00. .33. .00. .14. .00. .38. .00. .33. .00. .15. .00. .37. .00. A [0.9]. .33. .00. .52. .00. .28. .00. .33. .00. .56. .00. .27. .00. .33. .00. .52. .00. .28. .00. B [0.8]. .34. .00. .31. .00. .35. .00. .34. .00. .29. .00. .35. .00. .34. .00. .31. .00. .35. .00. C [0.7]. .33. .00. .17. .00. .37. .00. .33. .00. .16. .00. .38. .00. .33. .00. .17. .00. .37. .00. A [0.9]. .33. .00. .50. .00. .28. .00. .33. .00. .54. .00. .28. .00. .33. .00. .50. .00. .28. .00. B [0.8]. .34. .00. .31. .00. .35. .00. .34. .00. .29. .00. .35. .00. .34. .00. .32. .00. .35. .00. C [0.7]. .33. .00. .19. .00. .36. .00. .33. .00. .17. .00. .37. .00. .33. .00. .19. .00. .36. .00. FI 2 = . 1+2 = . MTL = . 86. FI 1 = .
(103) 1. 4-2-7. 2. 4% 3. SHOF. FI. 8%. MMM. FI. FI1+2. MMM. SHOF. MMM. 1%. MMM SHOF. MMM. FI. MMM FI1+2 SHOF. SHOF. MMM. MMM 2%. 6% 4-2-8. SHOF. FI 2%. MMM. FI. FI1+2 SHOF. MMM. MMM. 1%. MMM. SHOF. MMM. FI. MMM FI1+2. SHOF 87. MMM.
(104) SHOF. MMM. 2% 15 30 60 .98. 90. 1.00. 2. 4-2-9. 2 SHOF. FI. =120 MMM. FI. FI1+2 SHOF. 1.86. MMM. MMM. 0.16. MMM SHOF. MMM. FI. MMM SHOF. FI1+2 MMM. SHOF. MMM. = 120. 1.69. 3. 4-2-10. 2 SHOF .2 .89. MMM. .92. 4. 4-2-11. 2 SHOF 88.
(105) = 120. 36%. FI. MMM FI1+2. MMM. SHOF. MMM. 1%. MMM. SHOF. MMM. FI FI1+2. SHOF. MMM. SHOF. MMM. = 120. 33 5. 4-2-12. 2 MMM 1/3. SHOF. FI2. [0.9]. FI1. [0.7]. FI2. 6. 2 SHOF. MMM SHOF. MMM. FI. 89.
(106) 4-2-7. 2 SHOF. FI 1+2. MTL [. ]. MMM. FI 2. 11111. FI 1. SHOF. FI 1+2. FI 2. 11111 11111. FI 1. MMM. FI 1+2. FI 2. 11111 1. FI 1. SHOF. FI 1+2. Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD. MMM. FI 2. 1. FI 1. Mean SD Mean SD Mean SD. 30. .75 (1) [0.9] .81 (2) [0.8] .80 (3) [0.7] .81. .01 .01 .01 .01. .76 .85 .76 .73. .01 .01 .01 .01. .74 .78 .80 .82. .01 .02 .01 .01. .75 .79 .77 .78. .01 .01 .01 .02. .74 .79 .76 .73. .01 .01 .01 .01. .72 .75 .77 .78. .01 .01 .01 .02. .75 .81 .81 .81. .01 .02 .01 .01. .75 .81 .80 .81. .01 .02 .01 .01. .74 .80 .80 .81. .01 .01 .01 .01. .73 .78 .76 .77. .01 .01 .01 .01. .74 .78 .76 .77. .01 .01 .02 .02. .74 .78 .77 .77. .01 .01 .02 .01. 60. .77 (1) [0.9] .85 (2) [0.8] .84 (3) [0.7] .84. .01 .01 .01 .01. .77 .87 .83 .81. .01 .01 .01 .01. .77 .84 .85 .84. .01 .01 .01 .01. .75 .81 .80 .80. .01 .01 .01 .01. .75 .81 .82 .79. .01 .01 .01 .01. .75 .80 .81 .81. .01 .01 .01 .01. .78 .85 .84 .85. .01 .01 .02 .01. .78 .85 .83 .85. .01 .01 .01 .01. .78 .86 .82 .86. .01 .02 .02 .01. .75 .81 .81 .80. .01 .01 .01 .01. .76 .81 .81 .81. .01 .01 .01 .01. .76 .82 .81 .81. .01 .01 .01 .01. 90. .77 (1) [0.9] .86 (2) [0.8] .86 (3) [0.7] .86. .01 .01 .01 .01. .78 .88 .86 .84. .01 .01 .01 .01. .78 .86 .86 .86. .02 .01 .01 .01. .76 .83 .83 .82. .01 .01 .01 .01. .75 .81 .83 .81. .01 .01 .01 .01. .76 .82 .83 .82. .01 .01 .01 .01. .78 .86 .86 .86. .01 .01 .02 .01. .78 .85 .86 .86. .01 .01 .01 .01. .77 .87 .87 .86. .02 .01 .01 .01. .75 .83 .83 .82. .00 .01 .02 .01. .75 .83 .82 .82. .02 .01 .01 .01. .76 .83 .82 .82. .01 .01 .01 .02. 120. .78 (1) [0.9] .87 (2) [0.8] .88 (3) [0.7] .87. .01 .01 .01 .01. .78 .89 .88 .85. .01 .01 .01 .01. .78 .87 .87 .87. .01 .01 .01 .01. .75 .83 .83 .82. .01 .01 .02 .02. .74 .81 .83 .82. .01 .01 .01 .01. .77 .83 .83 .82. .01 .01 .01 .01. .78 .88 .87 .87. .01 .01 .01 .01. .78 .88 .88 .87. .01 .01 .01 .01. .77 .87 .88 .87. .01 .01 .01 .01. .76 .83 .82 .82. .01 .01 .01 .01. .76 .82 .82 .82. .01 .01 .01 .01. .76 .82 .83 .82. .01 .01 .01 .01. FI. FI 2 = . 1+2 = . MTL = . FI 1 = . SHOF = the Sympson and Hetter online procedure with Freeze MMM = the modified multinomial model. 90.
(107) 4-2-8. 2 11. 1MTL1. SHOF FI 1+2. MMM. FI 2. 11 FI 1. 1111 FI 1+2. SHOF. 11111. FI 2. 11111. FI 1. FI 1+2. MMM FI 2. 1111 FI 1. SHOF FI 1+2. MMM. FI 2. 11 FI 1. Mean. SD. Mean. SD. Mean. SD. 30. .95. .00. .96. .00. .94. .01. .96 .01 .96 .00 .95 .01. .95 .01 .95 .01 .95 .01. .96. .01. .96. .01. .96. .00. 60. .92. .00. .92. .01. .92. .01. .93 .01 .93 .01 .93 .01. .92 .01 .92 .01 .92 .01. .93. .01. .93. .01. .93. .01. 90. .91. .00. .91. .00. .90. .01. .92 .01 .92 .01 .91 .01. .90 .01 .91 .01 .91 .01. .92. .01. .92. .01. .92. .01. 120. .89. .01. .90. .01. .88. .01. .91 .01 .91 .01 .91 .01. .89 .01 .89 .01 .90 .01. .91. .01. .91. .01. .91. .01. FI. FI 2 = . 1+2 = . MTL = . 4-2-9. Mean SD Mean SD Mean SD. FI 1 = . SHOF = the Sympson and Hetter online procedure with Freeze MMM = the modified multinomial model. 2 SHOF. 1MTL1. Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD. 1. FI 1+2. MMM. FI 2. 11111 FI 1. Mean SD Mean SD Mean SD. FI 1+2. SHOF. 111111. FI 2. FI 1. Mean SD Mean SD Mean SD. 111111 FI 1+2. MMM FI 2. 111111 FI 1. Mean SD Mean SD Mean SD. 1. SHOF FI 1+2. FI 2. MMM. 1 FI 1. Mean SD Mean SD Mean SD. 30. 29.38 0.06 29.51 0.05 29.33 0.11 29.43 0.09 29.58 0.05 29.43 0.06 29.44 0.08 29.47 0.09 29.46 0.07 29.47 0.06 29.59 0.08 29.50 0.05. 60. 57.30 0.26 57.57 0.27 57.23 0.27 57.68 0.33 57.99 0.19 57.65 0.30 57.46 0.23 57.52 0.29 57.33 0.18 57.76 0.14 58.02 0.15 57.80 0.21. 90. 84.75 0.37 85.06 0.30 84.30 0.52 85.63 0.47 85.86 0.46 85.30 0.45 84.83 0.39 84.87 0.49 84.82 0.21 85.68 0.38 85.97 0.66 85.62 0.51. 120. 111.85 0.53 112.11 0.62 111.35 0.71 113.43 0.45 113.27 0.39 113.21 0.75 111.82 0.42 111.58 0.55 112.00 0.50 113.54 0.62 114.12 0.87 113.58 0.72. FI. FI 2 = . 1+2 = . MTL = . FI 1 = . SHOF = the Sympson and Hetter online procedure with Freeze MMM = the modified multinomial model. 91.
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