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表一 台灣地區民眾處理人際糾紛方式之次數分佈表
表二 各種潛在類別分析模式分析的結果
模式a L2 df
=.05 時 的決策
=.01 時
的決策
與財物有關
C4pa 258.404 208 拒絕 拒絕 .617 C4pb 295.768 204 拒絕 拒絕 .657 C3pa 132.456 54 拒絕 拒絕 .647 C2pa 13.311 6 拒絕 接受 .557 C2pb 14.608 6 拒絕 接受 .553
與財物無關
C4npa 212.386 205 接受 接受 .564 C4npb 202.320 206 接受 接受 .547 C3npa 61.825 54 接受 接受 .585 C2npa 5.939 6 接受 接受 .566 C2npb 16.166 6 拒絕 接受 .553
a 模式代號意義詳細內容請參考本論文「研究發現」中第二節「潛在類別 分析的結果」中的討論。
表三 在與財物有關的糾紛情況中使用「正式」與「非正式」社會控制方式（即 表二的 C2pa）機率及與實際變項的選項間的條件機率
實際變項 選項a
潛 在 正式
類 別
非正式 自己兄弟姊妹爭
遺產
使 用 與 法 律 有 關 的方式
.419 .059 使用與法律無關的
方式
.581 .941
參加互助會被倒 十萬元
使 用 與 法 律 有 關 的方式
.366 .065 使用與法律無關的
方式
.634 .935
買到瑕疵品，商 家不退換
使 用 與 法 律 有 關 的方式
.441 .060 使用與法律無關的
方式
.559 .940
車子與別人車子 相撞
使 用 與 法 律 有 關 的方式
.894 .492 使用與法律無關的
方式
.106 .508
Latent Class
Probabilities .334 .666
a關於實際變項的選項，請見本論文「研究方法與假設」中第三節「分析方法」
中的討論。
表四 在與財物無關的糾紛情況中使用「正式」與「非正式」社會控制方式兩潛 在類別（即表二的 C2npa）機率及與實際變項的選項間的條件機率
實際變項 選項a
潛 在 正式
類 別
非正式 配偶有外遇 使 用 與 法 律 有 關
的方式
.384 .121 使用與法律無關的
方式
.616 .879
小孩在學校被 老師體罰
使 用 與 法 律 有 關 的方式
.181 .019 使用與法律無關的
方式
.819 .981
老闆不按規定 改善工作條件
使 用 與 法 律 有 關 的方式
.720 .081 使用與法律無關的
方式
.280 .919
到餐廳吃飯吃 壞肚子
使 用 與 法 律 有 關 的方式
.602 .070 使用與法律無關的
方式
.398 .930
Latent Class
Probabilities .203 .797
a關於實際變項的選項，請見本論文「研究方法與假設」中第三節「分析方法」中的討論。
表五 社會關係結構因素與使用「正式」與「非正式」社會控制方式兩潛在類別 間邏輯迴歸分析的結果
社會關係 結構因素
與 財 B
務 有 關 S. E.
情 況 Exp (B)
與 財 B
務 無 S. E.
關 情 況 Exp (B)
男 性 .244 .144 1.276 .644* .188 1.905
年 齡 -.020* .008 .980 -.016 .010 .984
省 籍
本省閩南 a
本省客家 .132 .165 1.141 .208 .213 1.231
大陸省籍 .357* .166 1.429 .342 .214 1.408
其它 1.247* .373 3.476 .842 .455 2.320
已 婚 -1.45 .167 .866 .053 .217 1.054
教育程度 .215* .607 1.239 .228* .078 1.257
有職業者 -.165 .424 .848 -.042 .547 .959
社會階級
第一類 -.152 .582 .859 -.184 .731 .832
第二類 .032 .488 1.033 -.085 .618 .919
第三類 -.011 .438 .989 -.304 .563 .738
第四類 .069 .445 1.071 -.183 .572 .833
第五類 a
全家收入 .134 .110 1.143 -.089 .142 .915
都市化程度
都會區 -.646* .250 .524 -.656* .310 .519
城鎮區 -.380 .258 .684 -.371 .316 .690
鄉村區 a
人口密度 .052 .111 1.054 .026 .143 1.027
有治安機關 .240 .241 1.271 .212 .295 1.236
Constant -1.066 .526 -2.093 .668 N=1189 N=1187
-2 Log Likelihood=1409.686 -2 Log Likelihood=970.279 Goodness of Fit=1186.866 Goodness of Fit=1170.482 Model Chi-Squares=80.285 Model Chi-Squares=46.833
df=17, p<0.001 df=17, p<0.001 正確預測率 69.8% 正確預測率 84.5%
* p<0.05 a 參考組