Z[ J($%sË&‹+ÌÍp-./0123456789v+48êVÎÏ®.w 43.96B¯dSD¹2.66eIÎϺ»¼½w26.87B¯dSD¹2.46eIÎÏ2345w971.98
¶·dSD¹290.38eVSâ"ê JŸ+’5p<=ÑÒIÎÏ:;<=DE®.±f12B
¯V$%ŸR²—KL9:×wÓ\B½>ÔRTp&\ÕGIA+, JŸÐ(qrFR ÖIKLqr•×3-1Iõ@†‡•˜z
{>±²
ر²pX½RÙ³°I*($% JŸI´±w21êd43.80%e>³±w27ê d56.30%eV
~>º»¼½
*º»¼½&ÚI($% JŸ±f27¼Ÿv+25êd52.10%e>€f36p27¼Ÿv+
23êd47.90%eV
">2345
*2345&ÚI($%A1000¶·=wRÛÜI±f1000¶·Ÿv+27êd56.30%e
>€f1000p1500¶·Ÿv+21êd43.80%eV Š>¾D¿
($%$†3ùÝ‚Ä•F¾D¿ÛìaàRIRš•˜z d{eÀÁ£2Â
Þˆ(9:×wFX½RÙßDGI;DRp89+É‘•ÅÀÁ£2Âd45
êI93.70ÊeIñòzÀÁ£2Âw1ÅŸ+38êd79.20%e>ÀÁ£2Âw2ÅŸ+6ê d12.50%e>ÀÁ£2Âw3ÅŸ+1êd2.10%e‰cD3ÀÁ£2Âà+3êd6.30%eV
d~eÆÇÈÉ¿
ÆÇÈÉ¿&ÚIcá•ÆÇÈÉ¿Ÿâ+3êd6.30%eISãá•ÆÇÈÉ¿1ÅŸ 16êd33.30%e>2ÅŸ11êd22.90%e>3ÅŸ13êd27.10%e>4ÅŸ5êd10.40%eV
d"e̱ÍÎÏ
*$% JŸâIcD3̱ÍÎÏŸ37êd77.10%eI•+̱ÍÎÏŸƒ+11ê d22.90%eV
dŠeÐѱÍ<ÒÓÔ
Ø$%ˆ(â“eá•ÐѱÍ<ÒÓÔŸUäd42êI87.50%eI“cD3ÐѱÍ
<ÒÓÔŸƒâ+6êd12.50%eV dxehÕÖÏ×
$ JŸ9:×wFX½RÙqr³°Ià+4êd8.30Êe0123456789*†
3ù‚cá•hÕÖÏ׉“•+hÕÖÏ×1ÅŸv33êd68.80%e>hÕÖÏ×2ÅŸv 4êd8.30%e>hÕÖÏ×3ÅŸv7êd14.60%eV
x>hijk
($%$¨â¢Fq;-«¬FŠfgrstF`pvåqrI~01456789h ijkRwhØ>hØQÄÙ¾½>hØQÄ•ÅIAX½RÙptu&\ÕGˆ(*hi jkpGHV
d{ehØ
$012345F6789ª/hØÃÄJ„=w›mF9:×wIDGhØÃÄŸ+
3êd6.30%)IhØQÄŸƒUäI+45êd93.80%eV d~ehØQÄÙ¾½
§¨fgF`hijklmijIDG+æä6789ZÝÙ¾ÉZìçFàÝQÄI èƒZÝá•xhJyhIzƒxh”{ÝVMWRSWˆ(ËhØQÄÙ¾½FRÙID GÃÄŸv3êd6.30%e‰hØQÄÙ¾½wÚ{dÚéxh>yhz{ÝeŸv22ê
d45.80%e>hØQÄÙ¾½wÞÛdÙ¾ÞÛàÝQÄeŸv22êd45.80%e>hØQ
×3-1 -./01234567899:qrX½RÙ×
9:qr B½ ÔRT
1000!1500¶· 21 43.80%
µ27¼ 25 52.10%
27!36¼ 23 47.90%
Æ 3 6.30%
9:qr B½ ÔRT
hijk hØ
hØQÄÙ¾½
hØQÄ•Å
1Å 33 68.80%
2Å 4 8.30%
3Å 7 14.60%
ÃÄ 3 6.30%
QÄ 45 93.80%
ÃÄ 3 6.30%
Ú{dÚéxh>yh>{Ýe 22 45.80%
ÞÛdÙ¾ÞÛàÝQÄe 22 45.80%
"ÛdÙ¾"ÛàÝQÄe 1 2.10%
ÃÄ 3 6.30%
áÅ 25 52.10%
âÅ 13 27.10%
5Å 7 14.60%
!Šy $%bc
w>!-./012345F6789<=DEI($%X•PDMS-IIw$%bcJn o‹êFqrVA˜~ŽOPDMS-IIa€„I£ë;ì—3íŸ>ÌîO…>Ìîªp>Ì î£ë|}JïÌ&'> uR&'>ïÌ•‚>“RpuðJ©ñ>bcFò™ÅR²ó šFdFolio & Fewell, 2000eV
{>3íŸ
\FolioJFewellf2000®§¨SôŸõö÷ø<=DEZ×ùdPDMSe1úž²5#
Äû““pV
~>ÌîO…
ü•f0!6ýp{þù9BÑÒ89dChildren with DisabilitieseV
">픻p
d{e•JaðKOfZ®.8ÿpC4<=kØDEV
d~e•ARÐTU:<=J?@<=pkØDEIAlh8ÿ<=kØDER!pG…V d"e!"#$%&'()'*+,-./&012)345678+9:;
<=>?@,-AB"#CD+EDFG;
<H>?@IJKLMNdFolio & Fewell, 2000eV
Š>Ìî£ë|}JïÌ&'
PDMS-II £ëßRw:<=J?@<=RÌîIS˜"ß$¨#$첓R&%BRw ÌîV*:;<=RÌîD&Iñ8õãäù>õåæçèù>õéêùBõëìçèùŠ BwªI'89p<=DE®.±f12B¯ÝIAÌîõãäù>õåæçèùJõéêù
"RwÌîw•I(ê)üõëìçèùRwÌj89p<=DE®*;f12B¯;
Ìîw•V*?@<=RÌîD&Iñ8õîïùJõh<CÙùÞBwªI“ JïÌp 89êË&?@<=p‹+wªV
SÌî£ë•˜z d{e:<=RÌî
1. ãäzv8žIÌî8ÿO+,-NpÞ<ã.Vñò/0ãä•1óãä>ÉO2 3Ø4DãäpCÙIJÞ•ã.dautomatic reaction e•5675Ø89ã.
dLandau reactioneJúÛ:;˜<‡±ã.dprotecting reactionep+ÆJ=ÅV 2. åæçèzv30žIaZù9>?@>A4*5GF£IBBCÎDpkØVñò8
ÿpEDçè>F:çè>FG>H:çè>ÚIJ>IKJ>J:˜ûL<=>M NGFJ1Ã\OPQA‘kØV
3. éêzv89žIað8ÿ\{‘éRS{‘pkØVñòÐ(éê#$•zN:˜Š Tp<=J•5>…A>Uü<=>JG>VWXY>1ó>ÑZY>[Y‰\‘é ê#$•]ó>0.Y>ÑZXY>ߘ^_>`\>`y>`˜>`a>ÚI`>
Y9b>/c…>dóJ]ó`‘kØV
4. ëìçèzv24žIað8ÿíçú\ëìpkØVñò;ëJ±ëpe>f>g‘
#$p+ÆJ?hÅV d~e?@<=RÌî
1. îïzv26žIað8ÿŒ•ZpkØVñòîïãäpCÙ>îïçæpDE>O ficdjke>lmpíçkØ>ïnkØpDE>,ÐJºßoÿpkØV 2. h<CÙzv72žIaðù9›•heiJ)üpqpZfr›<=pkØVñòú
Û:;˜pHhkØ>Zfr›<=>sZpâb)ê>ttupvmí=>wl m>Lxlm>yzz>{|pï'JŒ•#$>}~J%•¯%pL4‘kØV
x>uR&'
PDMS-IIw"RZ×IúR½•^p_`•˜z
2z×GË€OÙ•^_`V
1z×G•‚샕^_`I„cOÙV
0zÉkzÉ…†ÍIck×G2‡Ì#$p73V
ˆBwªB²R½p•^_`I´‡•f*—~ßVŒ•ÝI*‰wªc“Š°Rd2 ReF/Iß5pÌÍ3XIA8ÿ‹“Šp–\R½J*—FV
‹>ïÌ•‚
wghïÌÝŽIïÌŒ• ŽA˜•ƒz d{eG0Üdentry pointse
Äûˆ(â75ÊZ.8ÿß•^pžªVOf{þù9ïÌŸß$8ÿp•‘®.>6 7ù$S’î.>ÑÒù9ƒ$8ÿpDE®.J2“ü'pïÌG0ÜV
d~eÐ`”dbasal levele
*wªâIÉ"S®.”Iâ•RßÌ“À?3B2RI–—Ð`”VÐ`”A˜pwª ÉŒïÌI€DA2RuðVïÌÝ\G0ÜûVIR˜™pwªûüIš“ŠÀ?"B 2RI–ß›?œRßÌI9Šß•”wžVšc—"B2RF/I+{Bwªw0z1RIƒ ê`ÇG0ÜF/pwªI9ŠLŠÐ`”IœÇŠU˜™pwªÌÍI9pß•”wžV d"eß•”dceiling levele
ÌÍûü•ß‹šI'—À?3B0R–wß•”Iß•”AßÉŒœïÌI´A0R uVWw•ƒI»•:<=pãäRwÌü•IãäRwÌî•Ÿ8ÿãäpCÙ
%I*•¡®.z’î.12B¯A˜ŸI´•¢žÌÍV
£>“RpuðJ©ñ
“RijpÕGARwÌîp/0R½dRaw Scorese>®.R½dAge
Equiva-d{e/0R½zúRwÌîp/0R½IwRwÌî£úBwª“Rp”|V
d~eRwÌî_`R½z~RwÌîp/0R½¥I$8ÿp•¡®.z’î.–ßm
×LŠ‰wR½K'p_`R½d0!20eISÎϦw10I_`Pw3V89‹“F _`R½*m×3-2Iß“eW89pkØ×GI_`R½§\I×°8ÿRw<=
kØDE¨©V
×3-2 PDMS-II_`R½Oª×
_`R½ dStandard Scorese
kØ«š
kجR-®dVery Superiore kØ-®dSuperiore
kد°\fZ®.8ÿp{þ±`dAbove Averagee kØ*{þ±`dAveragee
kد°².Z®.8ÿp{þ±`dBelow Averagee kØPdPoore
kسÄPdVery Poore
d"eRÌîDE¤½z~RÌ´RwÌî_`R½”|I–ß“:<=_`R½
¥>?@<=_`R½¥J|<=_`R½¥Vœ$_`R½¥m×I–ß“RÌî J|ÌîpDE¤½IÎϦw100I_`Pw15V89‹“FDE¤½*m×3-3I ß“eW89<=DEp×GIDE¤½§\I×°8ÿ<=DE¨©V
×3-3 PDMS-IIDE¤½Oª×
DE¤½ dQuotient Scorese
DE«š
DE¬R-®dVery Superiore DE-®dSuperiore
DE¯°\fZ®.8ÿp{þ±`dAbove Averagee DE*{þ±`dAveragee
DE¯°².Z®.8ÿp{þ±`dBelow Averagee DEPdPoore
DE³ÄPdVery Poore
µ>bcFò™Å d{eòÅ
PDMS-IIpòÅ••\"D&J>!z
1. £ëYˆdcontent samplingeI••*>!RwÌîJRÌªp{ì %IA
€DÄûˆ(pqrJRSVij³°Cronbach ! ¶½*RwÌî ! = 0.89!0.96IR ÌîJ|Ìî ! = 0.96!0.97I³•žªp{ìK'\V
2. ÝŽYˆdtime samplingeIA5Ì&\JRSIA_`R½¥¤½JaKL±p>
!I•JÞ·¸pÞ¹ù9wˆ(IÌS5ÌòÅI!{¹8ÿv20;I®.2!11 B¯Ir = 0.73!0.96‰!~¹8ÿv30;I®.12!17B¯Ir = 0.85!0.96V 3. ÌpPQdinterscorer differenceseI\Äûˆ(⺩223!11B¯;J15
!36B¯;p8ÿú30;IA_`R½aKL±p>! Ir = 0.96!0.99V qr³°PDMS-IIw{\òÅpaZbcV
d~e™Å
™Åqr\"&ÚJlhz
1. £ë«š™Å dcontent-description validityeI‹+PDMS-IIpwªIRwÌîJRw Ìî2“I’"л¼§½*'¾d1975!1996epDE’"IRwÌî••§¨
Harrow*1972®‹®2pG’<=RìI“RÌ§¨*îJ¿ÀRbJàRI .c+K'p×Ú™ÅV»ÕG’"лIFolioJFewelld2000esASÁtu&' JîÂS£ë™Åz
d1ewªRS'ditem analysiseA€DÄûˆ(pqrJlhIŒ•wªRS'Jw ªã.’"IAuðwªàÃØdàö½ r = 0.35!0.75eJwª˜™ÅI$WJ Ä2wªJÅ™wªpÆ‚V
d2eB²wªjkRS•••JlhwªpkPVŒ•€DÄûˆ(qrIAO½Ç Èdlogistic regressioneJaRSIlh|û\ƒ„³ÉP-fD&û\Ialpha¦¬
f0.001IijsÊ+wªMcOÙ“ËÌ»V
2. ™_•Ì™Ådcriterion-prediction validityeIPDMS-II v®ÍÞBZÝ™Åp¨z {wAPDMS=™_I30;1!11B¯;pù9IlÌ/.ŸPDMS“RijFKL
±I¨³°ÞŸ+\ÅKLIr = 0.84!0.91VS{ƒAÎÏÐ6‚-ÑZ× dMul-len Scales of Early LearningzAGS Editionew™_I29;2!66 B¯;pÒÓùwÔ ÍŸVij:<=ÌîKL¶½ r = 0.86I?@<=RÌîKL¶½ r = 0.80V
3. #}(Õ™Ådconstruct-identification validity eI*#}™ÅpRSßI••A"B
&ÚJ>!z
d1eî±MNRSdconfirmatory factor analysisez~€DÄûqrRwÞ¹R SI{w1!11B¯IMNRSý½wTLI=0.98Ix!/df =3.2IRMSEA=0.68‰S{¹ w12!71B¯pÒÓùÄûIý½ijwTLI=0.96Ix!/df =3.98IRMSEA=0.80Vq r³°—Š0Öü×Ådexcellent fiteV
d2e®.àÃzA6B®.¹RwÌîp/0R½ÎϦØKLI®.KL¶½ r
=0.80!0.93I³•c+®.àÃØV
d3eÙËàÃdgroup differentiationezTUÉZÙËŽpÎÏ_`R½VTUpÙ Ëñò±²d³>´ez³9J´9FŽÆ³ÉPQVÛÙz8ÚÛ>³Û>ÜÝ ÛÞ¢¶IijúÙËÎÏ_`R½´*ÃÄßà£VÑÒÙËIñòA4ÑÒJ ákÑÒIÎÏ_`R½´1fÎϦVij´••‚V
|iJ†I PDMS-II Æ"*ü•®.>Ìîªp>Ìîwª¼OÙ($%pªpIb PDMS-II wcâ©ò™ÅF_`[aðbcIk®Íã佨IghaðklIå”$%i jp(•±V(æ[$%bcõÒÓùçÙDEÌîùF<=RZ×ÌJPDMS-!Ì îžªKƒI§¨¢£$%DGÞaðbc+³ÉKL±dr = 0.47!0.84Ipµ0.001edè éꑶI2005eI³°PDMS-II <=DEpÄû¥¢£89<=DEÄûKLÅ\V¢£
ë+$%ŸŒ•PDMS-IIfÀ±ìíù9<=aðßIij³°PDMS-IIOÀ±ìíù9+
â©FœÌòÅdWang, Liao, & Hsieh, 2006eMWI($%2“PDMS-II w$%bcI•A ÌZ-./0123456789F<=DEV
!xy qrtuRS
+™ˆ(Fš—.I›•tuœ•ž4 SPSS for Mac 17.0 ⥟ûüqr‘’JtuR SVÙÙ$%ªpJ$%-žI2“ÙüpRS&'IRSÚ0•˜z
ö>«š±tuz
{>X½RÙdFrequency DistributioneBÔRTdPercentagee
†‡Ô̈(<=DEœH>³´¶½>2345>º»¼½>¾D¿>hijkFú ÛqrFRÖV
~>ÎϦdMeaneB_`PdStandard Deviatione
AÎϦJ_`PRS-./0123456789:;<=>?@<=JC4<=D E %IAǬ«¬-ž{V
'>î"±tuz
{> t l)dt Teste
d{e Ú{ˆ( t l)dOne-sample t Teste
Œ•Ú{ˆ( t l)RS-./0123456789:;<=>?@<=>C4<=
BSRwkØJPDMS-IIÄûƒ„+³ÉPQdp<0.05eIAǬ«¬-ž{V d~e ïðˆ( t l) dIndependent t Teste
Œ•ïðˆ( t l)R²TU-./0123456789*±²>2345>º»¼
½>ÀÁ£2Â>ÆÇÈÉ¿>̱ÍÎÏ>ÐѱÍ<ÒÓÔ>hijkF×wßIS:
;<=>?@<=>C4<=BSRwkØDEƒ„+³ÉPQñ*dp<0.05eI¡î$%
ò¬{pxIsǬ«¬-ž~V
~>ÚMÿ×Q½RSdOne Way ANOVAe
Œ•ÚMÿ×Q½RSlh-./0123456789*hÕÖÏ×F×wßIS:
;<=>?@<=>C4<=BSúwkØDE+ƳÉPQñ*dp<0.05eVšF¦—³ ɱ`dp<0.05eIœAéó'dScheff"e methodeûü-.TUI¡î$%ò¬ŠIsÇ
¬«¬-ž2-4V
!"# $%&'()*
+$%,-./0$%1234PDMS-II56789:;<=>?@ABCDEFGH IJKLMNOPLM4QRDLMSTUVW3XYZ[\]^_`a=>?@ABCD EFGHILMSTbcde\fghijkl+#mnj5op3!dp5=>?@AB CDEFGHILMSTUVW(jk3!qp5rsa=>?@ABCDEFGHILM STUfghijk3!tp5BCDEa=>?@ABCDEFGHILMSTUfgh ijk3!"p5uvwxa=>?@ABCDEFGHILMSTUfghijk3!y p5zS{a=>?@ABCDEFGHILMSTUfghijk3!|p5}~•€a
=>?@ABCDEFGHILMSTUfghijk3!op•5‚ƒ)*l„…†op M‡ˆj‰Š‹l
!dp =>?@ABCDEFGHILMSTUVW(jk
+pŒ•Ž‰=>?@ABCDEFGHIJKLMNOPLM4QRDLMSTUV W3Xcde••FGHI•JKLMNOPLM4QRDLMST(PDMS-II‘’\fg
“”34•–$%—˜1-1N1-2N1-3l&'j‰™‡š
›NJKLMSTVW
PDMS-II\JKLMjœ•3•žŸ ¡¢NŸ£¤¥¦¢NŸ§¨¢QŸ©ª¥¦¢
"«j¬œ•l•†-\$%®3mn6748¨=>?@ABCDEFGHI\LMST3
¯®°3¨HIJKLMST±>²³12«´3•PDMS-IIJKLMjœ•34µœŸ
¡¢NŸ£¤¥¦¢(Ÿ§¨¢t¬œ•5¶·¯¸45¨=>?@ABCDEFGHIJK LMST±>¹º»12«´3•PDMS-IIJKLMjœ••4µœŸ£¤¥¦¢NŸ§¨¢
QŸ©ª¥¦¢5¶l_†+$%\Ÿ ¡¢j¬œ•¼°3½¾¿3Ÿ£¤¥¦¢(Ÿ§
¨¢Àj¬œ•Á°48½¾¿3•Ÿ©ª¥¦¢j¬œ•Â•°45½¾¿l4‡…PDMS-IIŸ ¡¢NŸ£¤¥¦¢NŸ§¨¢QŸ©ª¥¦¢"¬j¬œ•(JKLMjœ•\&
'js)*jkš ÃdÄ ¡
™?ʼn3_°3¨Æ(†$%U=>?@ABCDEFGHILMST±>²³12«
´3Å4Ç°3ÈÃ100%ĵœŸ ¡¢¬É3†3È\ ¡STÊV¹Ë³Ÿ€ÌÍ‘
f¢3™Ê4-1l ÃqÄ£¤¥¦
Æ(+$%U=>?@ABCDEFGHI•Ÿ£¤¥¦¢j¬œ•®34€ÌÎÏ:
j3°18¨Ã37.5%Ä˳Ÿ€Ì•dÐÑÒÓº»dÐÑÒ ¢3°16¨Ã33.3%Ä˳ Ÿ€ÌÔÕÖ×[±>HØ\dÐÑÒ¢3°11¨Ã22.9%Ä˳Ÿ€Ìf¢3Ù×3¨
Ã6.3%Ä˳Ÿ€ÌÍ‘f¢3™Ê4-1l
&'ÚV37.5Û\$%Ü+•£¤¥¦ÝÞ3™ßà(áâãä\€Ì35å‘ST·
¯¸æ°62.5Û\$%Ü+LM€ÌA³[>\ã¹ÑÒl Ãtħ¨
Ÿ§¨¢ j¬œ•&'çè3°14¨Ã29.2%ÄÆ(†-$%\=>?@ABCDEF GHI§¨ST˳Ÿ€Ì•dÐÑÒÓº»dÐÑÒ¢3¯¸34Ã70.8ÛĨLM€ÌA
³[>\ã¹ÑÒl¯®Ö•Ÿ€ÌÔÕÖ×[±>HØ\dÐÑÒ¢\5Ùé3°19¨
Ã39.6%Ä·Ÿ€Ìf¢\5-U3°9¨Ã18.8%Ä·Ùê\•5Ÿ€ÌÍ‘f¢ë3¼°
6¨Ã12.6%Ä3™Ê4-1l
&'SV¼°ìí30Û\$%Ü+¯§¨€Ì˳å‘ST3îï70Û\$%Ü+§¨
€ÌA³[>\ã¹ÑÒl Ã"Ä©ª¥¦
°45¨$%Ü+ì🩪¥¦¢j¬œ•3SVŸ€Ì•dÐÑÒÓº»dÐÑÒ¢
ëÙé3°21¨Ã43.8%Ä·Y-5Ÿ€ÌÔÕÖ×[±>HØ\dÐÑÒ¢ë°19¨
Ã39.6%Ä·Ÿ€Ìf¢ë°3¨Ã6.3%Ä·ÈxÙê•5Ÿ€ÌÍ‘f¢ë3¼°2¨
Ã4.2%Ä3™Ê4-1l
Ê4-1 JKLMj¬œ•U-xj÷Ê
¡j¬œ•n=33£¤¥¦(§¨ j¬œ•n=483©ª¥¦j¬œ•n=45
3Ã100.0Ä 3Ã6.3Ä 6Ã12.5Ä 2Ã4.2Ä 0Ã0Ä 11Ã22.9Ä 9Ã18.8Ä 3Ã6.3Ä 0Ã0Ä 16Ã33.3Ä 19Ã39.6Ä 19Ã39.6Ä 0Ã0Ä 18Ã37.5Ä 14Ã29.2Ä 21Ã43.8Ä ¡j¬œ•n=33£¤¥¦(§¨ j¬œ•n=483©ª¥¦j¬œ•n=45
¡j¬œ•n=33£¤¥¦(§¨ j¬œ•n=483©ª¥¦j¬œ•n=45 ¡j¬œ•n=33£¤¥¦(§¨ j¬œ•n=483©ª¥¦j¬œ•n=45
ÃyÄJKLMRDST
Ê4-2 JKLMNOPLM(RDLMjœ•U-xj÷Ê
JKLMST OPLMST RDLMST
n(%) n(%) n(%)
8Ã16.7Ä 8Ã16.7Ä 10Ã20.8Ä 13Ã27.1Ä 13Ã27.1Ä 12Ã25.0Ä 17Ã35.4Ä 12Ã25.0Ä 15Ã31.3Ä 10Ã20.8Ä 15Ã31.3Ä 11Ã22.9Ä
‚ƒ4Â\$%&'üSV3ý³20.8Ûö43.8Û\$%Ü+•JKLMQ¯j¬€Ì ST5[>\dÐÑÒ3¯¸•4JKLMRDSTÂA³[>dÐÑÒ5Ùé°79.2Û3
©ª¥¦€Ì5Ùê3°56.2ÛFGHI€ÌA³[±>\dÐÑÒl
þN OPLMSTVW
PDMS-II\OPLMjœ•3•žŸÿ!¢(Ÿ}LRƒ¢À«j¬œ•3"°ST±
>Â\#¦3$«j¬œ•Á%&µœ3'()*OPLMjœ•l ÃdÄÿ!
•Ÿÿ!¢j¬œ•ÝÞ3Y€ÌÎÏ:j3Ÿ€Ì•dÐÑÒÓº»dÐÑÒ¢5Ù é3n°21¨Ã43.8%Ä·Ÿ€ÌÔÕÖ×[±>HØ\dÐÑÒ¢510¨Ã20.8%Ä·
Ÿ€Ìf¢°12¨Ã25.0%Ä·Ùו+Ÿ€ÌÍ‘f¢ë3°5¨Ã10.4%Ä3™Ê4-3l
&'çè°43.8Û$%Ü+Uÿ!€ÌÊVïdÐÑÒÓº»dÐÑÒl ÃqÄ}LRƒ
Æ(†-$%U=>?@ABCDEFGHI•Ÿ}LRƒ¢j¬€ÌSTÂ34Ÿ€
Ì•dÐÑÒÓº»dÐÑÒ¢5Ùé3n°20¨Ã47.1%Ä3¯-5Ÿ€ÌÔÕÖ×[±
>HØ\dÐÑÒ¢n14¨Ã29.2%Ä3Ÿ€Ìf¢°10¨Ã20.8%Ä3Ùê•+Ÿ€ÌÍ
‘f¢ë3¼°4¨Ã8.3%Ä3™Ê4-3l ÃtÄOPLMRDST
Yhô:,Æ(†-$%U=>?@ABCDEFGHI\OPLMRDST3-Ùé hô\+ŸST•dÐÑÒÓº»dÐÑÒ¢3n15¨Ã31.3%Ä 3¯-+ŸSTf¢n13
¨Ã27.1%Ä3ŸSTÔÕÖ×[±>HØ\dÐÑÒ¢n12¨Ã25.0%Ä3Ùê\+ŸS TÍ‘f¢3°8¨Ã16.7%Ä3™Ê4-2Åèl
]i³JKLMST3$%Ü+•OPLM\ÊVi.343.8Û\FGHI¯ÿ!€Ì STï[±>\dÐÑÒ3}LRƒ\ST•/î3°47.1Û\FGHIï[>UdÐÑ Ò·01OPLMRDSTï2[>dÐÑÒ\hôZ™ÿ!(}LRƒ€Ì334°
31.3Û\FGHIï2[>HI5°\STÊV3î³JKLMRDST\20.8Ûlû»6 23$%ëSV$%Ü+¯OPLMSTï2[>dÐÑÒ\hôiJKLMSTîl78
Ê4-3 OPLMj¬œ•U-xj÷Ê
5Ã10.4Ä 4Ã8.3Ä
12Ã25.0Ä 10Ã20.8Ä 10Ã20.8Ä 14Ã29.2Ä 21Ã43.8Ä 20Ã47.1Ä