Table 4 Logistic Regression Analysis

X1

2.093***

(8.106)

.667***

(1.948)

2.398***

(10.997)

.459**

(1.582)

2.327***

(10.245)

.375*

(1.455)

1.797***

(6.030)

.409**

(1.506)

X2

−.439

(.645)

.357

(1.429)

.239

(1.270)

.153

(1.165)

−.011

(.989

−.038

(.962

−.292

(.747)

.229

(1.257)

X3

2.643**

(14.052)

−.085

(.918)

1.983

(7.262)

−.054

(.948)

1.823

(6.189)

.053

(.898)

2.159*

(8.662)

−.365

(.694)

M1

−.179

(.836)

.657***

(1.930)

.900

(2.460)

.469**

(1.598)

M2

−.911

(.402)

−.807***

(.446)

.781

(2.184)

−1.516**

(.220

M3

.274

(1315)

.419

(1.520)

−19.131

(.000)

−.485

(.411)

C

.004

(1.004)

.002

(1.002)

.003

(1.003)

.001

(1.001)

.005

(1.005)

.002

(.1.002)

.002

(1.002)

.000

(.936)

X1*M1

−1.386

(.250)

.234

(1.264)

X2*M1

−1.771

(.170)

.215

(1.24)

X3*M1

19.829

(409037997)

−.271

(.762)

X1*M2

−2.167

(.115)

1.207**

(3.342

X2*M2

−.740

(.477

.992

(2.696

X3*M2

20.100

(536195041)

−.54

(.583)

X1*M3

39.928

(8.056E + 16)

.448

(.641)

X2*M3

−21.075

(.000)

.463

(.641)

X3*M3

19.695

(357697811)

1.186

(.231)

−2LL

73.657***

718.859***

70.790***

727.93**

70.389***

723.009***

71.440***

733.2*

NR ²

.411

.069

.446

.047

.451

.059

.439

.035

HL

.539

.936

.701

.334

.508

.483

.530

.517