MIXED scorta BY Dyadwin_1 WITH Kips_mean_centered

(1)

MIXED scorta BY Dyadwin_1 WITH Kips_mean_centered

/CRITERIA=CIN(95) MXITER(100) MXSTEP(10) SCORING(1) SINGULAR(0.000000000001 ) HCONVERGE(0,

ABSOLUTE) LCONVERGE(0, ABSOLUTE) PCONVERGE(0.000001, ABSOLUTE)

/FIXED=Dyadwin_1 Kips_mean_centered Dyadwin_1*Kips_mean_centered | SSTYPE(3) /METHOD=REML

/PRINT=CORB COVB G R SOLUTION TESTCOV

/REPEATED=Dyadwin | SUBJECT(Dyad) COVTYPE(DIAG).

Mixed Model Analysis

Model Dimension^a Number of

Levels

Covariance Structure

Number of Parameters

Subject Variables

Number of Subjects Fixed Effects Intercept

Dyadwin_1 Kips_mean_centered

Dyadwin_1 * Kips_mean_centered

Repeated Effects Dyadwin Total

1 1

2 1

1 1

2 1

2 Diagonal 2 Dyad 50

8 6

Dependent Variable: scorta.

a.

Information Criteria

^a

-2 Restricted Log Likelihood Akaike's Information Criterion (AIC)

Hurvich and Tsai's Criterion (AICC)

Bozdogan's Criterion (CAIC) Schwarz's Bayesian Criterion (BIC)

-8.852 -4.852

-4.722

2.256 .256

The information criteria are displayed in

smaller-is-better form.

(2)

Type III Tests of Fixed Effects

^a

Source Numerator df Denominator df F Sig.

Intercept Dyadwin_1

Kips_mean_centered

Dyadwin_1 * Kips_mean_centered

1 93.566 422.963 .000

1 93.566 .002 .967

1 93.625 2.168 .144

1 93.625 3.994 .049

Dependent Variable: scorta.

a.

Estimates of Fixed Effects^a

Parameter Estimate Std. Error df t Sig.

95% Confidence Interval Lower Bound Upper Bound Intercept

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

Kips_mean_centered [Dyadwin_1=.00] * Kips_mean_centered [Dyadwin_1=1.00] * Kips_mean_centered

.445379 .032249 47 13.810 .000 .380501 .510256

-.001779 .043226 93.566 -.041 .967 -.087609 .084052

0^b 0 . . . . .

.015766 .044671 47 .353 .726 -.074101 .105634

-.119798 .059945 93.625 -1.998 .049 -.238827 -.000769

0^b 0 . . . . .

a.

This parameter is set to zero because it is redundant.

b.

Correlation Matrix for Estimates of Fixed Effects^a

Parameter Intercept

[Dyadwin_1=.

00]

[Dyadwin_1=1.

00]

Kips_mean_ce ntered

[Dyadwin_1=.

00] * Kips_mean_ce

ntered

[Dyadwin_1=1.

00] * Kips_mean_ce

ntered Intercept

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

1 -.746 .^b .017 -.013 .^b

-.746 1 .^b -.013 .010 .^b

.^b .^b .^b .^b .^b .^b

.017 -.013 .^b 1 -.745 .^b

-.013 .010 .^b -.745 1 .^b

.^b .^b .^b .^b .^b .^b

a.

(3)

Covariance Matrix for Estimates of Fixed Effects^a

Parameter Intercept

[Dyadwin_1=.

00]

[Dyadwin_1=1.

00]

Kips_mean_ce ntered

[Dyadwin_1=.

00] * Kips_mean_ce

ntered

[Dyadwin_1=1.

00] * Kips_mean_ce

ntered Intercept

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

.001040 -.001040 0^b 2.520214E-5 -2.520214E-5 0^b

-.001040 .001868 0^b -2.520214E-5 2.516049E-5 0^b

0^b 0^b 0^b 0^b 0^b 0^b

2.520214E-5 -2.520214E-5 0^b .001996 -.001996 0^b

-2.520214E-5 2.516049E-5 0^b -.001996 .003593 0^b

0^b 0^b 0^b 0^b 0^b 0^b

a.

The covariance is set to zero because it is associated with a redundant parameter.

b.

Covariance Parameters

Estimates of Covariance Parameters^a

Parameter Estimate Std. Error Wald Z Sig.

95% Confidence Interval Lower Bound Upper Bound Repeated Measures Var: [Dyadwin=.0000]

Var: [Dyadwin=1.0000]

.050946 .010509 4.848 .000 .034003 .076330

.041421 .008455 4.899 .000 .027763 .061798

a.

Correlation Matrix for Estimates of Covariance Parameters

^a

Parameter

Repeated Measures Var:

[Dyadwin=.

0000]

Var:

[Dyadwin=1.

0000]

Repeated Measures Var: [Dyadwin=.0000]

Var: [Dyadwin=1.0000]

1 .000

.000 1

Dependent Variable: scorta.

a.

(4)

Covariance Matrix for Estimates of Covariance Parameters

^a

Parameter

Repeated Measures Var:

[Dyadwin=.

0000]

Var:

[Dyadwin=1.

0000]

Repeated Measures Var: [Dyadwin=.0000]

Var: [Dyadwin=1.0000]

.000110 .000000

.000000 7.148781E-5 Dependent Variable: scorta.

a.

Residual Covariance (R) Matrix

^a

[Dyadwin = .

0000]

[Dyadwin = 1.0000]

[Dyadwin = .0000]

[Dyadwin = 1.0000]

.050946 0

0 .041421

Diagonal

Dependent Variable: scorta.

a.

MIXED scorta BY Dyadwin_1 WITH Kips_mean_centered

/CRITERIA=CIN(95) MXITER(100) MXSTEP(10) SCORING(1) SINGULAR(0.000000000001 ) HCONVERGE(0,

ABSOLUTE) LCONVERGE(0, ABSOLUTE) PCONVERGE(0.000001, ABSOLUTE)

/FIXED=Dyadwin_1 Kips_mean_centered Dyadwin_1*Kips_mean_centered | SSTYPE(3) /METHOD=REML

/PRINT=CORB COVB G R SOLUTION TESTCOV

/REPEATED=Dyadwin | SUBJECT(Dyad) COVTYPE(ID).

Selected Model for Cortisol AM

Mixed Model Analysis

(5)

Levels

Subject Variables

1 1

2 1

1 1

2 1

2 Identity 1 Dyad 50

8 5

a.

Information Criteria

^a

-2 Restricted Log Likelihood Akaike's Information Criterion (AIC)

Hurvich and Tsai's Criterion (AICC)

Bozdogan's Criterion (CAIC) Schwarz's Bayesian Criterion (BIC)

-8.344 -6.344

-6.301 -2.790 -3.790 The information criteria are displayed in smaller-is-better form.

Dependent Variable: scorta.

a.

Fixed Effects

Type III Tests of Fixed Effects

^a

Source Numerator df Denominator df F Sig.

Intercept Dyadwin_1

Kips_mean_centered

Dyadwin_1 * Kips_mean_centered

1 95 423.870 .000

1 95 .002 .967

1 95 2.172 .144

1 95 4.001 .048

(6)

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

.445379 .030688 95 14.513 .000 .384455 .506303

-.001779 .043179 95 -.041 .967 -.087500 .083943

0^b 0 . . . . .

.015766 .042509 95 .371 .712 -.068625 .100158

-.119798 .059889 95 -2.000 .048 -.238693 -.000903

0^b 0 . . . . .

a.

b.

Parameter Intercept

[Dyadwin_1=.

00]

[Dyadwin_1=1.

00]

Kips_mean_ce ntered

[Dyadwin_1=.

00] * Kips_mean_ce

ntered

[Dyadwin_1=1.

00] * Kips_mean_ce

ntered Intercept

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

1 -.711 .^b .017 -.012 .^b

-.711 1 .^b -.012 .009 .^b

.^b .^b .^b .^b .^b .^b

.017 -.012 .^b 1 -.710 .^b

-.012 .009 .^b -.710 1 .^b

.^b .^b .^b .^b .^b .^b

a.

The correlation is system missing because it is associated with a redundant parameter.

b.

(7)

Parameter Intercept

[Dyadwin_1=.

00]

[Dyadwin_1=1.

00]

Kips_mean_ce ntered

[Dyadwin_1=.

00] * Kips_mean_ce

ntered

[Dyadwin_1=1.

00] * Kips_mean_ce

ntered Intercept

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

.000942 -.000942 0^b 2.282150E-5 -2.282150E-5 0^b

-.000942 .001864 0^b -2.282150E-5 2.277513E-5 0^b

0^b 0^b 0^b 0^b 0^b 0^b

2.282150E-5 -2.282150E-5 0^b .001807 -.001807 0^b

-2.282150E-5 2.277513E-5 0^b -.001807 .003587 0^b

0^b 0^b 0^b 0^b 0^b 0^b

a.

b.

Covariance Parameters

Estimates of Covariance Parameters^a

95% Confidence Interval Lower Bound Upper Bound Repeated Measures Variance .046133 .006694 6.892 .000 .034714 .061308

a.

Correlation Matrix for Estimates of Covariance Parameters

^a

Parameter

Repeated Measures Variance

Repeated Measures Variance 1

Dependent Variable: scorta.

a.

Covariance Matrix for Estimates of Covariance

Parameters

^a

(8)

Residual Covariance (R) Matrix

^a

[Dyadwin = .

0000]

[Dyadwin = 1.0000]

[Dyadwin = .0000]

[Dyadwin = 1.0000]

.046133 0

0 .046133

Identity

Dependent Variable: scorta.

a.

MIXED scorta BY Dyadwin_1 WITH Kips_mean_centered

/CRITERIA=CIN(95) MXITER(100) MXSTEP(10) SCORING(1) SINGULAR(0.000000000001 ) HCONVERGE(0,

ABSOLUTE) LCONVERGE(0, ABSOLUTE) PCONVERGE(0.000001, ABSOLUTE)

/FIXED=Dyadwin_1 Kips_mean_centered Dyadwin_1*Kips_mean_centered | SSTYPE(3) /METHOD=REML

/PRINT=CORB COVB G R SOLUTION TESTCOV

/REPEATED=Dyadwin | SUBJECT(Dyad) COVTYPE(CS).

Mixed Model Analysis

Levels

Subject Variables

Repeated Effects Dyadwin

Total

1 1

2 1

1 1

2 1

2 Compound

Symmetry 2 Dyad 50

8 6

a.

(9)

Information Criteria

^a

-2 Restricted Log Likelihood Akaike's Information Criterion (AIC)

Hurvich and Tsai's Criterion (AICC)

Bozdogan's Criterion (CAIC) Schwarz's Bayesian Criterion (BIC)

-11.998 -7.998

-7.868 -.891 -2.891 The information criteria are displayed in smaller-is-better form.

Dependent Variable: scorta.

a.

Fixed Effects

Type III Tests of Fixed Effects

^a

Source Numerator df Denominator df F Sig.

Intercept Dyadwin_1

Kips_mean_centered

Dyadwin_1 * Kips_mean_centered

1 47.243 333.873 .000

1 46.961 .010 .922

1 47.126 1.619 .210

1 46.845 5.722 .021

Dependent Variable: scorta.

a.

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

Kips_mean_centered [Dyadwin_1=.00] *

.447221 .030681 88.610 14.577 .000 .386255 .508187

-.003620 .036784 46.961 -.098 .922 -.077622 .070381

0^b 0 . . . . .

.017969 .042507 88.490 .423 .674 -.066498 .102437

(10)

Parameter Intercept

[Dyadwin_1=.

00]

[Dyadwin_1=1.

00]

Kips_mean_ce ntered

[Dyadwin_1=.

00] * Kips_mean_ce

ntered

[Dyadwin_1=1.

00] * Kips_mean_ce

ntered Intercept

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

1 -.607 .^b .016 -.013 .^b

-.607 1 .^b -.013 .011 .^b

.^b .^b .^b .^b .^b .^b

.016 -.013 .^b 1 -.606 .^b

-.013 .011 .^b -.606 1 .^b

.^b .^b .^b .^b .^b .^b

a.

b.

Parameter Intercept

[Dyadwin_1=.

00]

[Dyadwin_1=1.

00]

Kips_mean_ce ntered

[Dyadwin_1=.

00] * Kips_mean_ce

ntered

[Dyadwin_1=1.

00] * Kips_mean_ce

ntered Intercept

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

.000941 -.000685 0^b 2.108789E-5 -2.110075E-5 0^b

-.000685 .001353 0^b -2.110075E-5 2.106719E-5 0^b

0^b 0^b 0^b 0^b 0^b 0^b

2.108789E-5 -2.110075E-5 0^b .001807 -.001313 0^b

-2.110075E-5 2.106719E-5 0^b -.001313 .002601 0^b

0^b 0^b 0^b 0^b 0^b 0^b

a.

b.

Covariance Parameters

95% Confidence Interval Lower Bound Upper Bound Repeated Measures CS diagonal offset

CS covariance

.033385 .006923 4.822 .000 .022235 .050126

.012797 .007065 1.811 .070 -.001049 .026644

a.

(11)

Correlation Matrix for Estimates of Covariance Parameters

^a

Parameter

Repeated Measures CS diagonal

offset CS covariance Repeated Measures CS diagonal offset

CS covariance

1 -.505

-.505 1

Dependent Variable: scorta.

a.

Covariance Matrix for Estimates of Covariance Parameters

^a

Parameter

Repeated Measures CS diagonal

offset CS covariance Repeated Measures CS diagonal offset

CS covariance

4.792580E-5 -2.471807E-5 -2.471807E-5 4.990962E-5 Dependent Variable: scorta.

a.

Residual Covariance (R) Matrix

^a

[Dyadwin = .

0000]

[Dyadwin = 1.0000]

[Dyadwin = .0000]

[Dyadwin = 1.0000]

.046182 .012797

.012797 .046182

Compound Symmetry

Dependent Variable: scorta.

a.

MIXED scorta BY Dyadwin_1 WITH Kips_mean_centered

/CRITERIA=CIN(95) MXITER(100) MXSTEP(10) SCORING(1) SINGULAR(0.000000000001 ) HCONVERGE(0,

ABSOLUTE) LCONVERGE(0, ABSOLUTE) PCONVERGE(0.000001, ABSOLUTE)

/FIXED=Dyadwin_1 Kips_mean_centered Dyadwin_1*Kips_mean_centered | SSTYPE(3)

(12)

Levels

Subject Variables

1 1

2 1

1 1

2 1

2 Unstructured 3 Dyad 50

8 7

a.

Information Criteria

^a

-2 Restricted Log Likelihood Akaike's Information Criterion (AIC)

Hurvich and Tsai's Criterion (AICC)

Bozdogan's Criterion (CAIC) Schwarz's Bayesian Criterion (BIC)

-12.561 -6.561

-6.298 4.100 1.100 The information criteria are displayed in smaller-is-better form.

Dependent Variable: scorta.

a.

Fixed Effects

Type III Tests of Fixed Effects

^a

Source Numerator df Denominator df F Sig.

Intercept Dyadwin_1

Kips_mean_centered

Dyadwin_1 * Kips_mean_centered

1 47.040 332.981 .000

1 46.819 .011 .917

1 46.921 1.604 .212

1 46.716 5.743 .021

Dependent Variable: scorta.

a.

(13)

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

.447445 .032266 46.915 13.867 .000 .382530 .512359

-.003844 .036806 46.819 -.104 .917 -.077895 .070207

0^b 0 . . . . .

.018237 .044704 46.879 .408 .685 -.071701 .108175

-.122269 .051022 46.716 -2.396 .021 -.224927 -.019610

0^b 0 . . . . .

a.

b.

Parameter Intercept

[Dyadwin_1=.

00]

[Dyadwin_1=1.

00]

Kips_mean_ce ntered

[Dyadwin_1=.

00] * Kips_mean_ce

ntered

[Dyadwin_1=1.

00] * Kips_mean_ce

ntered Intercept

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

1 -.660 .^b .016 -.014 .^b

-.660 1 .^b -.014 .012 .^b

.^b .^b .^b .^b .^b .^b

.016 -.014 .^b 1 -.658 .^b

-.014 .012 .^b -.658 1 .^b

.^b .^b .^b .^b .^b .^b

a.

b.

(14)

Parameter Intercept

[Dyadwin_1=.

00]

[Dyadwin_1=1.

00]

Kips_mean_ce ntered

[Dyadwin_1=.

00] * Kips_mean_ce

ntered

[Dyadwin_1=1.

00] * Kips_mean_ce

ntered Intercept

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

.001041 -.000784 0^b 2.328562E-5 -2.329856E-5 0^b

-.000784 .001355 0^b -2.329856E-5 2.326986E-5 0^b

0^b 0^b 0^b 0^b 0^b 0^b

2.328562E-5 -2.329856E-5 0^b .001998 -.001502 0^b

-2.329856E-5 2.326986E-5 0^b -.001502 .002603 0^b

0^b 0^b 0^b 0^b 0^b 0^b

a.

b.

Covariance Parameters

95% Confidence Interval Lower Bound Upper Bound Repeated Measures UN (1,1)

UN (2,1) UN (2,2)

.051080 .010563 4.836 .000 .034059 .076606

.012872 .007059 1.823 .068 -.000964 .026708

.041421 .008455 4.899 .000 .027763 .061798

a.

Correlation Matrix for Estimates of Covariance Parameters

^a

Parameter

Repeated Measures UN (1,1) UN (2,1) UN (2,2) Repeated Measures UN (1,1)

UN (2,1) UN (2,2)

1 .387 .077

.387 1 .372

.077 .372 1

Dependent Variable: scorta.

a.

(15)

Covariance Matrix for Estimates of Covariance Parameters

^a

Parameter

Repeated Measures

UN (1,1) UN (2,1) UN (2,2) Repeated Measures UN (1,1)

UN (2,1) UN (2,2)

.000112 2.882628E-5 6.903583E-6 2.882628E-5 4.983250E-5 2.221535E-5 6.903583E-6 2.221535E-5 7.148779E-5 Dependent Variable: scorta.

a.

Residual Covariance (R) Matrix

^a

[Dyadwin = .

0000]

[Dyadwin = 1.0000]

[Dyadwin = .0000]

[Dyadwin = 1.0000]

.051080 .012872

.012872 .041421

Unstructured

Dependent Variable: scorta.

a.

MIXED logcortp2 BY Dyadwin_1 WITH Kips_mean_centered

/CRITERIA=CIN(95) MXITER(100) MXSTEP(10) SCORING(1) SINGULAR(0.000000000001 ) HCONVERGE(0,

ABSOLUTE) LCONVERGE(0, ABSOLUTE) PCONVERGE(0.000001, ABSOLUTE)

/FIXED=Dyadwin_1 Kips_mean_centered Dyadwin_1*Kips_mean_centered | SSTYPE(3) /METHOD=REML

/PRINT=CORB COVB G R SOLUTION TESTCOV

/REPEATED=Dyadwin | SUBJECT(Dyad) COVTYPE(UN).

Mixed Model Analysis

(16)

Levels

Subject Variables

1 1

2 1

1 1

2 1

2 Unstructured 3 Dyad 49

8 7

Dependent Variable: logcortp2.

a.

Information Criteria

^a

-2 Restricted Log Likelihood Akaike's Information Criterion (AIC)

Hurvich and Tsai's Criterion (AICC)

Bozdogan's Criterion (CAIC) Schwarz's Bayesian Criterion (BIC)

79.745 85.745

86.015 96.343 93.343 The information criteria are displayed in smaller-is-better form.

Dependent Variable: logcortp2.

a.

Fixed Effects

Type III Tests of Fixed Effects

^a

Source Numerator df Denominator df F Sig.

Intercept Dyadwin_1

Kips_mean_centered

Dyadwin_1 * Kips_mean_centered

1 45.313 474.098 .000

1 45.563 2.684 .108

1 45.337 1.683 .201

1 45.572 3.677 .061

Dependent Variable: logcortp2.

a.

(17)

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

-1.068102 .047333 47.000 -22.566 .000 -1.163324 -.972880

.088691 .054135 45.563 1.638 .108 -.020305 .197686

0^b 0 . . . . .

-.012552 .065499 47.000 -.192 .849 -.144319 .119215

-.143717 .074952 45.572 -1.917 .061 -.294626 .007192

0^b 0 . . . . .

a.

b.

Parameter Intercept

[Dyadwin_1=.

00]

[Dyadwin_1=1.

00]

Kips_mean_ce ntered

[Dyadwin_1=.

00] * Kips_mean_ce

ntered

[Dyadwin_1=1.

00] * Kips_mean_ce

ntered Intercept

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

1 -.298 .^b -.016 .005 .^b

-.298 1 .^b .005 -.036 .^b

.^b .^b .^b .^b .^b .^b

-.016 .005 .^b 1 -.297 .^b

.005 -.036 .^b -.297 1 .^b

.^b .^b .^b .^b .^b .^b

a.

b.

(18)

Parameter Intercept

[Dyadwin_1=.

00]

[Dyadwin_1=1.

00]

Kips_mean_ce ntered

[Dyadwin_1=.

00] * Kips_mean_ce

ntered

[Dyadwin_1=1.

00] * Kips_mean_ce

ntered Intercept

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

.002240 -.000762 0^b -5.061781E-5 1.722481E-5 0^b

-.000762 .002931 0^b 1.722481E-5 -.000147 0^b

0^b 0^b 0^b 0^b 0^b 0^b

-5.061781E-5 1.722481E-5 0^b .004290 -.001460 0^b

1.722481E-5 -.000147 0^b -.001460 .005618 0^b

0^b 0^b 0^b 0^b 0^b 0^b

a.

b.

Covariance Parameters

95% Confidence Interval Lower Bound Upper Bound Repeated Measures UN (1,1)

UN (2,1) UN (2,2)

.109752 .022640 4.848 .000 .073253 .164439

.072405 .023541 3.076 .002 .026265 .118544

.175793 .037231 4.722 .000 .116072 .266241

a.

Correlation Matrix for Estimates of Covariance Parameters

^a

Parameter

Repeated Measures UN (1,1) UN (2,1) UN (2,2) Repeated Measures UN (1,1)

UN (2,1) UN (2,2)

1 .634 .265

.634 1 .666

.265 .666 1

Dependent Variable: logcortp2.

a.

(19)

Covariance Matrix for Estimates of Covariance Parameters

^a

Parameter

Repeated Measures UN (1,1) UN (2,1) UN (2,2) Repeated Measures UN (1,1)

UN (2,1) UN (2,2)

.000513 .000338 .000223 .000338 .000554 .000584 .000223 .000584 .001386 Dependent Variable: logcortp2.

a.

Residual Covariance (R) Matrix

^a

[Dyadwin = .

0000]

[Dyadwin = 1.0000]

[Dyadwin = .0000]

[Dyadwin = 1.0000]

.109752 .072405

.072405 .175793

Unstructured

Dependent Variable: logcortp2.

a.

MIXED logcortp2 BY Dyadwin_1 WITH Kips_mean_centered

/CRITERIA=CIN(95) MXITER(100) MXSTEP(10) SCORING(1) SINGULAR(0.000000000001 ) HCONVERGE(0,

ABSOLUTE) LCONVERGE(0, ABSOLUTE) PCONVERGE(0.000001, ABSOLUTE)

/FIXED=Dyadwin_1 Kips_mean_centered Dyadwin_1*Kips_mean_centered | SSTYPE(3) /METHOD=REML

/PRINT=CORB COVB G R SOLUTION TESTCOV

/REPEATED=Dyadwin | SUBJECT(Dyad) COVTYPE(CS).

Selected Model for Cortisol PM

Mixed Model Analysis

(20)

Levels

Subject Variables

Total

1 1

2 1

1 1

2 1

2 Compound

Symmetry 2 Dyad 49

8 6

a.

Information Criteria

^a

-2 Restricted Log Likelihood Akaike's Information Criterion (AIC)

Hurvich and Tsai's Criterion (AICC)

Bozdogan's Criterion (CAIC) Schwarz's Bayesian Criterion (BIC)

83.123 87.123

87.257 94.189 92.189 The information criteria are displayed in smaller-is-better form.

Dependent Variable: logcortp2.

a.

Fixed Effects

Type III Tests of Fixed Effects

^a

Source Numerator df Denominator df F Sig.

Intercept Dyadwin_1

Kips_mean_centered

Dyadwin_1 * Kips_mean_centered

1 45.968 482.266 .000

1 45.460 2.532 .118

1 45.990 1.639 .207

1 45.481 3.492 .068

Dependent Variable: logcortp2.

a.

(21)

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

-1.068102 .053755 74.003 -19.870 .000 -1.175211 -.960993

.086285 .054227 45.460 1.591 .118 -.022903 .195474

0^b 0 . . . . .

-.012552 .074385 74.003 -.169 .866 -.160767 .135663

-.140296 .075073 45.481 -1.869 .068 -.291456 .010865

0^b 0 . . . . .

a.

b.

Parameter Intercept

[Dyadwin_1=.

00]

[Dyadwin_1=1.

00]

Kips_mean_ce ntered

[Dyadwin_1=.

00] * Kips_mean_ce

ntered

[Dyadwin_1=1.

00] * Kips_mean_ce

ntered Intercept

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

1 -.496 .^b -.016 .008 .^b

-.496 1 .^b .008 -.033 .^b

.^b .^b .^b .^b .^b .^b

-.016 .008 .^b 1 -.496 .^b

.008 -.033 .^b -.496 1 .^b

.^b .^b .^b .^b .^b .^b

a.

b.

(22)

Parameter Intercept

[Dyadwin_1=.

00]

[Dyadwin_1=1.

00]

Kips_mean_ce ntered

[Dyadwin_1=.

00] * Kips_mean_ce

ntered

[Dyadwin_1=1.

00] * Kips_mean_ce

ntered Intercept

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

.002890 -.001446 0^b -6.528365E-5 3.267778E-5 0^b

-.001446 .002941 0^b 3.267778E-5 -.000133 0^b

0^b 0^b 0^b 0^b 0^b 0^b

-6.528365E-5 3.267778E-5 0^b .005533 -.002770 0^b

3.267778E-5 -.000133 0^b -.002770 .005636 0^b

0^b 0^b 0^b 0^b 0^b 0^b

a.

b.

Covariance Parameters

95% Confidence Interval Lower Bound Upper Bound Repeated Measures CS diagonal offset

CS covariance

.070854 .014924 4.748 .000 .046890 .107065

.070698 .023626 2.992 .003 .024392 .117004

a.

Correlation Matrix for Estimates of Covariance Parameters

^a

Parameter

Repeated Measures CS diagonal

offset CS covariance Repeated Measures CS diagonal offset

CS covariance

1 -.339

-.339 1

Dependent Variable: logcortp2.

a.

Covariance Matrix for Estimates of Covariance Parameters

^a

Repeated Measures

CS diagonal

(23)

Residual Covariance (R) Matrix

^a

[Dyadwin = .

0000]

[Dyadwin = 1.0000]

[Dyadwin = .0000]

[Dyadwin = 1.0000]

.141552 .070698

.070698 .141552

Compound Symmetry

Dependent Variable: logcortp2.

a.

MIXED logcortp2 BY Dyadwin_1 WITH Kips_mean_centered

/CRITERIA=CIN(95) MXITER(100) MXSTEP(10) SCORING(1) SINGULAR(0.000000000001 ) HCONVERGE(0,

ABSOLUTE) LCONVERGE(0, ABSOLUTE) PCONVERGE(0.000001, ABSOLUTE)

/FIXED=Dyadwin_1 Kips_mean_centered Dyadwin_1*Kips_mean_centered | SSTYPE(3) /METHOD=REML

/PRINT=CORB COVB G R SOLUTION TESTCOV

/REPEATED=Dyadwin | SUBJECT(Dyad) COVTYPE(DIAG).

Mixed Model Analysis

Levels

Subject Variables

1 1

2 1

1 1

2 1

8 6

a.

(24)

Information Criteria

^a

-2 Restricted Log Likelihood Akaike's Information Criterion (AIC)

Hurvich and Tsai's Criterion (AICC)

Bozdogan's Criterion (CAIC) Schwarz's Bayesian Criterion (BIC)

93.352 97.352

97.485 104.417 102.417 The information criteria are displayed in smaller-is-better form.

Dependent Variable: logcortp2.

a.

Fixed Effects

Type III Tests of Fixed Effects

^a

Source Numerator df Denominator df F Sig.

Intercept Dyadwin_1

Kips_mean_centered

Dyadwin_1 * Kips_mean_centered

1 87.843 725.942 .000

1 87.843 1.065 .305

1 87.819 2.143 .147

1 87.819 1.504 .223

Dependent Variable: logcortp2.

a.

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

-1.068102 .047333 47 -22.566 .000 -1.163324 -.972880

.078789 .076361 87.843 1.032 .305 -.072966 .230544

0^b 0 . . . . .

-.012552 .065499 47 -.192 .849 -.144319 .119215

-.129633 .105707 87.819 -1.226 .223 -.339709 .080442

0^b 0 . . . . .

(25)

Parameter Intercept

[Dyadwin_1=.

00]

[Dyadwin_1=1.

00]

Kips_mean_ce ntered

[Dyadwin_1=.

00] * Kips_mean_ce

ntered

[Dyadwin_1=1.

00] * Kips_mean_ce

ntered Intercept

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

1 -.620 .^b -.016 .010 .^b

-.620 1 .^b .010 -.030 .^b

.^b .^b .^b .^b .^b .^b

-.016 .010 .^b 1 -.620 .^b

.010 -.030 .^b -.620 1 .^b

.^b .^b .^b .^b .^b .^b

a.

b.

Parameter Intercept

[Dyadwin_1=.

00]

[Dyadwin_1=1.

00]

Kips_mean_ce ntered

[Dyadwin_1=.

00] * Kips_mean_ce

ntered

[Dyadwin_1=1.

00] * Kips_mean_ce

ntered Intercept

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

.002240 -.002240 0^b -5.061781E-5 5.061781E-5 0^b

-.002240 .005831 0^b 5.061781E-5 -.000240 0^b

0^b 0^b 0^b 0^b 0^b 0^b

-5.061781E-5 5.061781E-5 0^b .004290 -.004290 0^b

5.061781E-5 -.000240 0^b -.004290 .011174 0^b

0^b 0^b 0^b 0^b 0^b 0^b

a.

b.

Covariance Parameters

95% Confidence Interval Lower Bound Upper Bound Repeated Measures Var: [Dyadwin=.0000] .109752 .022640 4.848 .000 .073253 .164439

(26)

Correlation Matrix for Estimates of Covariance Parameters

^a

Parameter

Repeated Measures Var:

[Dyadwin=.

0000]

Var:

[Dyadwin=1.

0000]

Repeated Measures Var: [Dyadwin=.0000]

Var: [Dyadwin=1.0000]

1 .000

.000 1

Dependent Variable: logcortp2.

a.

Covariance Matrix for Estimates of Covariance Parameters

^a

Parameter

Repeated Measures Var:

[Dyadwin=.

0000]

Var:

[Dyadwin=1.

0000]

Repeated Measures Var: [Dyadwin=.0000]

Var: [Dyadwin=1.0000]

.000513 .000000

.000000 .001288 Dependent Variable: logcortp2.

a.

Residual Covariance (R) Matrix

^a

[Dyadwin = .

0000]

[Dyadwin = 1.0000]

[Dyadwin = .0000]

[Dyadwin = 1.0000]

.109752 0

0 .172096

Diagonal

Dependent Variable: logcortp2.

a.

MIXED logcortp2 BY Dyadwin_1 WITH Kips_mean_centered

/CRITERIA=CIN(95) MXITER(100) MXSTEP(10) SCORING(1) SINGULAR(0.000000000001 ) HCONVERGE(0,

ABSOLUTE) LCONVERGE(0, ABSOLUTE) PCONVERGE(0.000001, ABSOLUTE)

/FIXED=Dyadwin_1 Kips_mean_centered Dyadwin_1*Kips_mean_centered | SSTYPE(3)

(27)

Levels

Subject Variables

1 1

2 1

1 1

2 1

8 5

a.

Information Criteria

^a

-2 Restricted Log Likelihood Akaike's Information Criterion (AIC)

Hurvich and Tsai's Criterion (AICC)

Bozdogan's Criterion (CAIC) Schwarz's Bayesian Criterion (BIC)

95.688 97.688

97.732 101.221 100.221 The information criteria are displayed in smaller-is-better form.

Dependent Variable: logcortp2.

a.

Fixed Effects

Type III Tests of Fixed Effects

^a

Source Numerator df Denominator df F Sig.

Intercept Dyadwin_1

Kips_mean_centered

Dyadwin_1 * Kips_mean_centered

1 93 729.427 .000

1 93 1.070 .304

1 93 2.153 .146

1 93 1.511 .222

(28)

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

-1.068102 .053572 93 -19.938 .000 -1.174485 -.961719

.078789 .076178 93 1.034 .304 -.072486 .230064

0^b 0 . . . . .

-.012552 .074132 93 -.169 .866 -.159762 .134659

-.129633 .105447 93 -1.229 .222 -.339029 .079763

0^b 0 . . . . .

a.

b.

Parameter Intercept

[Dyadwin_1=.

00]

[Dyadwin_1=1.

00]

Kips_mean_ce ntered

[Dyadwin_1=.

00] * Kips_mean_ce

ntered

[Dyadwin_1=1.

00] * Kips_mean_ce

ntered Intercept

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

1 -.703 .^b -.016 .011 .^b

-.703 1 .^b .011 -.027 .^b

.^b .^b .^b .^b .^b .^b

-.016 .011 .^b 1 -.703 .^b

.011 -.027 .^b -.703 1 .^b

.^b .^b .^b .^b .^b .^b

a.

b.

(29)

Parameter Intercept

[Dyadwin_1=.

00]

[Dyadwin_1=1.

00]

Kips_mean_ce ntered

[Dyadwin_1=.

00] * Kips_mean_ce

ntered

[Dyadwin_1=1.

00] * Kips_mean_ce

ntered Intercept

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

.002870 -.002870 0^b -6.483958E-5 6.483958E-5 0^b

-.002870 .005803 0^b 6.483958E-5 -.000220 0^b

0^b 0^b 0^b 0^b 0^b 0^b

-6.483958E-5 6.483958E-5 0^b .005495 -.005495 0^b

6.483958E-5 -.000220 0^b -.005495 .011119 0^b

0^b 0^b 0^b 0^b 0^b 0^b

a.

b.

Covariance Parameters

a.

Correlation Matrix for Estimates of Covariance Parameters

^a

Parameter

Repeated Measures Variance

Repeated Measures Variance 1

Dependent Variable: logcortp2.

a.

Covariance Matrix for Estimates of Covariance

Parameters

^a

(30)

Residual Covariance (R) Matrix

^a

[Dyadwin = .

0000]

[Dyadwin = 1.0000]

[Dyadwin = .0000]

[Dyadwin = 1.0000]

.140589 0

0 .140589

Identity

Dependent Variable: logcortp2.

a.

MIXED Logstesta BY Dyadwin_1 WITH Kips_mean_centered

/CRITERIA=CIN(95) MXITER(100) MXSTEP(10) SCORING(1) SINGULAR(0.000000000001 ) HCONVERGE(0,

ABSOLUTE) LCONVERGE(0, ABSOLUTE) PCONVERGE(0.000001, ABSOLUTE)

/FIXED=Dyadwin_1 Kips_mean_centered Dyadwin_1*Kips_mean_centered | SSTYPE(3) /METHOD=REML

/PRINT=CORB COVB G R SOLUTION TESTCOV

/REPEATED=Dyadwin | SUBJECT(Dyad) COVTYPE(ID).

Mixed Model Analysis

Levels

Subject Variables

1 1

2 1

1 1

2 1

8 5

Dependent Variable: Logstesta.

a.

(31)

Information Criteria

^a

-2 Restricted Log Likelihood Akaike's Information Criterion (AIC)

Hurvich and Tsai's Criterion (AICC)

Bozdogan's Criterion (CAIC) Schwarz's Bayesian Criterion (BIC)

6.312 8.312

8.357 11.834 10.834 The information criteria are displayed in smaller-is-better form.

Dependent Variable: Logstesta.

a.

Fixed Effects

Type III Tests of Fixed Effects

^a

Source Numerator df Denominator df F Sig.

Intercept Dyadwin_1

Kips_mean_centered

Dyadwin_1 * Kips_mean_centered

1 92 4670.069 .000

1 92 36.102 .000

1 92 4.965 .028

1 92 4.879 .030

Dependent Variable: Logstesta.

a.

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

Kips_mean_centered [Dyadwin_1=.00] *

1.759783 .033471 92 52.576 .000 1.693306 1.826261

-.284444 .047340 92 -6.009 .000 -.378466 -.190423

0^b 0 . . . . .

-.000640 .047024 92 -.014 .989 -.094033 .092753

(32)

Parameter Intercept

[Dyadwin_1=.

00]

[Dyadwin_1=1.

00]

Kips_mean_ce ntered

[Dyadwin_1=.

00] * Kips_mean_ce

ntered

[Dyadwin_1=1.

00] * Kips_mean_ce

ntered Intercept

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

1 -.707 .^b -.019 .014 .^b

-.707 1 .^b .014 .004 .^b

.^b .^b .^b .^b .^b .^b

-.019 .014 .^b 1 -.715 .^b

.014 .004 .^b -.715 1 .^b

.^b .^b .^b .^b .^b .^b

a.

b.

Parameter Intercept

[Dyadwin_1=.

00]

[Dyadwin_1=1.

00]

Kips_mean_ce ntered

[Dyadwin_1=.

00] * Kips_mean_ce

ntered

[Dyadwin_1=1.

00] * Kips_mean_ce

ntered Intercept

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

.001120 -.001120 0^b -3.017267E-5 3.017267E-5 0^b

-.001120 .002241 0^b 3.017267E-5 1.133865E-5 0^b

0^b 0^b 0^b 0^b 0^b 0^b

-3.017267E-5 3.017267E-5 0^b .002211 -.002211 0^b

3.017267E-5 1.133865E-5 0^b -.002211 .004323 0^b

0^b 0^b 0^b 0^b 0^b 0^b

a.

b.

Covariance Parameters

a.

(33)

Correlation Matrix for Estimates of Covariance Parameters

^a

Parameter

Repeated Measures Variance

Repeated Measures Variance 1

Dependent Variable: Logstesta.

a.

Covariance Matrix for Estimates of Covariance Parameters

^a

Parameter

Repeated Measures Variance Repeated Measures Variance 6.282101E-5

Dependent Variable: Logstesta.

a.

Residual Covariance (R) Matrix

^a

[Dyadwin = .

0000]

[Dyadwin = 1.0000]

[Dyadwin = .0000]

[Dyadwin = 1.0000]

.053757 0

0 .053757

Identity

Dependent Variable: Logstesta.

a.

MIXED Logstesta BY Dyadwin_1 WITH Kips_mean_centered

/CRITERIA=CIN(95) MXITER(100) MXSTEP(10) SCORING(1) SINGULAR(0.000000000001 ) HCONVERGE(0,

ABSOLUTE) LCONVERGE(0, ABSOLUTE) PCONVERGE(0.000001, ABSOLUTE)

/FIXED=Dyadwin_1 Kips_mean_centered Dyadwin_1*Kips_mean_centered | SSTYPE(3)

(34)

Mixed Model Analysis

Levels

Subject Variables

1 1

2 1

1 1

2 1

8 6

a.

Information Criteria

^a

-2 Restricted Log Likelihood Akaike's Information Criterion (AIC)

Hurvich and Tsai's Criterion (AICC)

Bozdogan's Criterion (CAIC) Schwarz's Bayesian Criterion (BIC)

-6.259 -2.259

-2.124 4.785 2.785 The information criteria are displayed in smaller-is-better form.

Dependent Variable: Logstesta.

a.

Fixed Effects

Type III Tests of Fixed Effects

^a

Source Numerator df Denominator df F Sig.

Intercept Dyadwin_1

Kips_mean_centered

Dyadwin_1 * Kips_mean_centered

1 74.238 4669.657 .000

1 74.238 36.099 .000

1 75.278 5.022 .028

1 75.278 4.934 .029

(35)

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

1.759783 .023927 46.000 73.548 .000 1.711621 1.807946

-.284444 .047342 74.238 -6.008 .000 -.378771 -.190118

0^b 0 . . . . .

-.000640 .033615 46.000 -.019 .985 -.068303 .067022

-.145230 .065379 75.278 -2.221 .029 -.275464 -.014995

0^b 0 . . . . .

a.

b.

Parameter Intercept

[Dyadwin_1=.

00]

[Dyadwin_1=1.

00]

Kips_mean_ce ntered

[Dyadwin_1=.

00] * Kips_mean_ce

ntered

[Dyadwin_1=1.

00] * Kips_mean_ce

ntered Intercept

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

1 -.505 .^b -.019 .010 .^b

-.505 1 .^b .010 .015 .^b

.^b .^b .^b .^b .^b .^b

-.019 .010 .^b 1 -.514 .^b

.010 .015 .^b -.514 1 .^b

.^b .^b .^b .^b .^b .^b

a.

b.

(36)

Parameter Intercept

[Dyadwin_1=.

00]

[Dyadwin_1=1.

00]

Kips_mean_ce ntered

[Dyadwin_1=.

00] * Kips_mean_ce

ntered

[Dyadwin_1=1.

00] * Kips_mean_ce

ntered Intercept

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

.000572 -.000572 0^b -1.541825E-5 1.541825E-5 0^b

-.000572 .002241 0^b 1.541825E-5 4.639207E-5 0^b

0^b 0^b 0^b 0^b 0^b 0^b

-1.541825E-5 1.541825E-5 0^b .001130 -.001130 0^b

1.541825E-5 4.639207E-5 0^b -.001130 .004274 0^b

0^b 0^b 0^b 0^b 0^b 0^b

a.

b.

Covariance Parameters

95% Confidence Interval Lower Bound Upper Bound Repeated Measures Var: [Dyadwin=.0000]

Var: [Dyadwin=1.0000]

.027470 .005728 4.796 .000 .018254 .041337

.080043 .016690 4.796 .000 .053191 .120452

a.

Correlation Matrix for Estimates of Covariance Parameters

^a

Parameter

Repeated Measures Var:

[Dyadwin=.

0000]

Var:

[Dyadwin=1.

0000]

Repeated Measures Var: [Dyadwin=.0000]

Var: [Dyadwin=1.0000]

1 .000

.000 1

Dependent Variable: Logstesta.

a.

(37)

Covariance Matrix for Estimates of Covariance Parameters

^a

Parameter

Repeated Measures Var:

[Dyadwin=.

0000]

Var:

[Dyadwin=1.

0000]

Repeated Measures Var: [Dyadwin=.0000]

Var: [Dyadwin=1.0000]

3.280784E-5 .000000 .000000 .000279 Dependent Variable: Logstesta.

a.

Residual Covariance (R) Matrix

^a

[Dyadwin = .

0000]

[Dyadwin = 1.0000]

[Dyadwin = .0000]

[Dyadwin = 1.0000]

.027470 0

0 .080043

Diagonal

Dependent Variable: Logstesta.

a.

MIXED Logstesta BY Dyadwin_1 WITH Kips_mean_centered

/CRITERIA=CIN(95) MXITER(100) MXSTEP(10) SCORING(1) SINGULAR(0.000000000001 ) HCONVERGE(0,

ABSOLUTE) LCONVERGE(0, ABSOLUTE) PCONVERGE(0.000001, ABSOLUTE)

/FIXED=Dyadwin_1 Kips_mean_centered Dyadwin_1*Kips_mean_centered | SSTYPE(3) /METHOD=REML

/PRINT=CORB COVB G R SOLUTION TESTCOV

/REPEATED=Dyadwin | SUBJECT(Dyad) COVTYPE(CS).

Mixed Model Analysis

(38)

Levels

Subject Variables

Total

1 1

2 1

1 1

2 1

2 Compound

Symmetry 2 Dyad 49

8 6

a.

Information Criteria

^a

-2 Restricted Log Likelihood Akaike's Information Criterion (AIC)

Hurvich and Tsai's Criterion (AICC)

Bozdogan's Criterion (CAIC) Schwarz's Bayesian Criterion (BIC)

5.872 9.872

10.006 16.915 14.915 The information criteria are displayed in smaller-is-better form.

Dependent Variable: Logstesta.

a.

Fixed Effects

Type III Tests of Fixed Effects

^a

Source Numerator df Denominator df F Sig.

Intercept Dyadwin_1

Kips_mean_centered

Dyadwin_1 * Kips_mean_centered

1 44.367 4240.940 .000

1 44.152 40.611 .000

1 44.840 4.696 .036

1 44.617 5.254 .027

Dependent Variable: Logstesta.

a.

(39)

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

1.760948 .033476 91.035 52.604 .000 1.694453 1.827443

-.286015 .044881 44.152 -6.373 .000 -.376458 -.195572

0^b 0 . . . . .

-.003256 .047022 91.160 -.069 .945 -.096657 .090144

-.142958 .062367 44.617 -2.292 .027 -.268602 -.017315

0^b 0 . . . . .

a.

b.

Parameter Intercept

[Dyadwin_1=.

00]

[Dyadwin_1=1.

00]

Kips_mean_ce ntered

[Dyadwin_1=.

00] * Kips_mean_ce

ntered

[Dyadwin_1=1.

00] * Kips_mean_ce

ntered Intercept

[Dyadwin_1=.00]

[Dyadwin_1=1.00]

1 -.670 .^b -.019 .015 .^b

-.670 1 .^b .015 .003 .^b

.^b .^b .^b .^b .^b .^b

-.019 .015 .^b 1 -.680 .^b

.015 .003 .^b -.680 1 .^b

.^b .^b .^b .^b .^b .^b

a.

b.