WARNING: 1. Because group sizes vary, the chi square difference tests involving diversity, contrast, and group effects are approximate. GROUP ACTOR-PARTNER INTERDEPENDENCE MODEL The group composition variable is Gender, a dichotomy consisting of Women and Men, and the outcome variable is Group Identification. The variable Gender is presumed to affect Group Identification in four different ways: the effect of the actor's own Gender or X, the effect of other group members' Gender or X', the effect of the similarity of the actor's Gender to the other group members' Gender or I, and the effect of the similarity of the others' Gender or I'. All of these variables are effect coded. For instance, X is coded Women = +1 and Men = -1. Any group which contains missing data on Gender is dropped from the analysis. RESULTS Descriptives For the analysis, there are 263 persons in 58 groups. The group sizes range from 3 and 5. There are 2 all-Men groups and 14 all-Women groups. There are 95 (36.1%) Men and 168 (63.9%) Women. The means and standard deviations are presented in Table 1. Complete Model The effect of the actor's Gender is .004 (p = .958). Women score .008 units higher on Group Identification than Men. The effect of the Gender of the other group members' is -.189 (p = .181). An actor, all of whose other group members are Women, scores .379 units lower on Group Identification than a member all of whose other members are Men. The effect of the actor's similarity to others in the group on Gender is .248 (p = .050). An actor, who is totally similar to the other group members on Gender, scores .496 units higher on Group Identification than an actor who is totally dissimilar. The effect of the others' similarity in Gender is -.105 (p = .425). In a 3-person group, a person with others who are completely homogeneous, either all Women or Men, scores .210 units lower on Group Identification than a person with 1 Women and 1 Men others. The variance due to groups is equal to .107 and the proportion of variance due to group or intraclass correlation is equal to .089. The multiple correlation explained by the four GAPIM-I fixed effects is equal to .090. The chi square test with four degrees of freedom that compares the Complete Model to the Empty Model equals 6.629 (p = .157). Because this chi square test is not statistically significant, we do not have evidence that any of the terms of the Complete Model are non-zero. The chi square test with two degrees of freedom that compares the Complete Model to the Main Effects Model equals 4.405 (p = .354). Because this chi square test is not statistically significant, we do not have evidence that the interaction effects of the Complete Model are non-zero. The sample size adjusted BIC for the Complete Model is 793.26 whereas the value for the Empty Model is 796.22. Because the index is smaller, the Complete Model is a better fitting model than the Empty Model. The Best Fitting Model The best fitting model is the Contrast (Main Effects and Interaction) Model with a multiple R of .105. This implies that there is a contrast effect both for the effect of Gender and the effects of similarity. The chi square test comparing this model to the Empty Model is equal to 5.159 with 2 degrees of freedom (p = .076). The sample size adjusted BIC is equal to 792.898. Table 1: Descriptive Statistics Variable Mean Standard Deviation -------------------------------------------------------- Gender .278 .963 Group Identification 4.102 1.102 Table 2: Model Estimates and Fit Model X X' I I' SABIC R ----------------------------------------------------------------------------------------------------------- Empty 0 0 0 0 796.224 Main Effects .049 -.172 0 0 795.833 .029 Actor Only .038 0 0 0 796.872 .000 Others Only 0 -.162 0 0 795.375 .055 Group -.139 -.139 0 0 796.066 .019 Contrast .076 -.076 0 0 795.760 .036 Complete .004 -.189 .248* -.105 793.261 .090 Person Fit .003 -.235+ .243+ 0 793.012 .096 Diversity .039 -.205 .094 .094 796.456 .000 Contrast .018 -.138 .180+ -.180+ 793.015 .102 Constaints on both Main Effects and Interactions Actor Only .002 0 .185 0 795.516 .000 Others Only 0 -.123 0 -.087 795.889 .000 Group -.189 -.189 .107 .107 796.606 .000 Contrast .045 -.045 .181+ -.181+ 792.898 .105 Actor and Others Similarity .046 0 0 -.146+ 796.318 .000 Others and Person Fit 0 -.123 .244* 0 792.097 .114 Table 3: Chi Square Tests Model Tested Chi Square df p ------------------------------------------------------ EMPTY MODEL AS THE COMPARISON MODEL (significant means a better fitting model) Main Effects 2.224 2 .329 Actor Only .269 1 .604 Others Only 1.766 1 .184 Group 1.075 1 .300 Contrast 1.381 1 .240 Complete 6.629 4 .157 Person Fit 5.962 3 .113 Diversity 2.517 3 .472 Contrast 5.959 3 .114 Constraints on both Main Effects and Interactions Actor Only 2.541 2 .281 Others Only 2.168 2 .338 Group 1.451 2 .484 Contrast 5.159 2 .076 Actor and Others' Similarity 1.739 2 .419 Others and Person Fit 5.960 2 .051 MAIN EFFECTS MODEL AS THE COMPARISON MODEL (significant means a worse fitting model) Actor Only 1.955 1 .162 Others Only .458 1 .498 Group 1.149 1 .284 Contrast .843 1 .359 COMPLETE MODEL AS THE COMPARISON MODEL (significant means a worse fitting model) Person Fit .667 1 .414 Diversity 4.112 1 .043 Contrast .670 1 .413 Constraints on both Main Effects and Interactions Actor Only 4.088 2 .130 Others Only 4.461 2 .107 Group 5.178 2 .075 Contrast 1.470 2 .480 Actor and Others' Similarity 4.890 2 .087 Others and Person Fit .669 2 .716