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Large-scale Assessments in Education

An IERI – International Educational Research Institute Journal

Table 3 Parameter estimates for terminal nodes from Mplus tree with complexity parameter of 0.01

From: A comparison of three approaches to covariate effects on latent factors

Parameter

Node 2

Node 3

SC.BY BSBM19A

1.000

1.000

SC.BY BSBM19C

0.823

1.529

SC.BY BSBM19D

1.105

1.361

SC.BY BSBM19E

0.442

0.852

SC.BY BSBM19F

1.060

1.346

SC.BY BSBM19G

0.895

0.943

SC.BY BSBM19I

0.702

1.216

BSBM19C.WITH BSBM19E

0.315

0.126

BSBM19C.WITH BSBM19I

0.365

0.101

BSBM19E.WITH BSBM19I

0.379

0.230

Intercepts BSBM19A

2.920

3.540

Intercepts BSBM19C

2.237

3.083

Intercepts BSBM19D

2.604

3.177

Intercepts BSBM19E

2.608

3.044

Intercepts BSBM19F

2.419

3.000

Intercepts BSBM19G

2.553

2.862

Intercepts BSBM19I

2.255

2.847

Variances SC

0.555

0.245

Residual.Variances BSBM19A

0.335

0.184

Residual.Variances BSBM19C

0.858

0.416

Residual.Variances BSBM19D

0.290

0.226

Residual.Variances BSBM19E

1.017

0.704

Residual.Variances BSBM19F

0.390

0.275

Residual.Variances BSBM19G

0.667

0.716

Residual.Variances BSBM19I

0.846

0.536

  1. The stopping criteria for tree growth were a maximum tree depth of four, a minimum number of observations in any terminal node of 100, and complexity parameter (cp) = 0.01. The first factor loading was fixed to 1 for model identification. Node 2 was the group of students in mathematics achievement categories 1, 2, and 3. Node 3 was the group of students in mathematics achievement categories 4 and 5
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