WARNING: 1. With covariates, ApimDText can fail to remove missing cases on the covariates. The researcher should remove those cases before undertaking the analysis. Actor-Partner Interdependence Model for Husband and Wife The focus of this study is the investigation of the effect of Other Positivity on Satisfaction and how that effect differs for Husband and Wife. Both the effect of own Other Positivity (actor) and the effect of partner's Other Positivity (partner) on Husband's and Wife's Satisfaction are studied. There are a total of 148 dyads with no missing data, each with one Husband and one Wife. The total number of individuals is 296. The means and standard deviations for Husband and Wife are presented in Table 1. There is one covariate that is controlled in all analyses. The covariate explains a statistically significant amount of variance of Satisfaction controlling for actor and partner effects (.035 proportion of the total variance for the Husband and .011 proportion for the Wife), chi square test with 1 degree of freedom equal to 6.126 (p = .013). RESULTS Actor Effects The actor effect for Husband is equal to .374 and is statistically significant (p < .001), with a small effect size (beta = .289), and the actor effect for Wife is equal to .523 and is statistically significant (p < .001), with a medium effect size (beta = .404). (See Table 2 for the actor effect estimates.) The difference between these two actor effects is not statistically significant (p = .312). Partner Effects The partner effect from Wife to Husband is equal to .372 and is statistically significant (p < .001), with a small effect size (beta = .242). The partner effect from Husband to Wife is equal to .261 and is statistically significant (p = .005), with a small effect size (beta = .201). (See Table 2 for the partner effect estimates.) The difference between these two partner effects is not statistically significant (p = .454). Actor-Partner Interactions The actor-partner interaction for Husband Satisfaction is equal to -.214 and is not statistically significant (p = .322). The partner effect for persons who are one standard deviation above the mean on Other Positivity is .261 and for persons who are one standard deviation below the mean on Other Positivity is .485. Additionally, the actor-partner interaction Wife Satisfaction is equal to -.134 and is not statistically significant (p = .523). The partner effect for persons who are one standard deviation above the mean on Other Positivity is .202 and for persons who are one standard deviation below the mean on Other Positivity is .324. The difference between the Husband and Wife interaction effects is not statistically significant (p = .711). The effect of the absolute difference of the two members on Other Positivity for Husband's Satisfaction is equal to -.095 and is not statistically significant (p = .491). Thus, if two members have the same score on Other Positivity, their score on Husband's Satisfaction is .095 units higher than it is for a dyad whose scores on Satisfaction differ by one unit. The effect of the absolute difference of the two members on Other Positivity for Wife's Satisfaction is equal to -.073 and is not statistically significant (p = .585). Thus, if two members have the same score on Other Positivity, their score on Wife's Satisfaction is .073 units higher than it is for a dyad whose scores on Satisfaction differ by one unit. The difference between these two discrepancy effects is not statistically significant (p = .876). Effect of the Distinguishing Variable The predicted score on Satisfaction for those who score zero on Other Positivity is 3.608 for Husband and 3.583 for Wife and that difference is not statistically significant (p = .620), with a less than small effect size (d = .043). Relation of Actor and Partner Effects An analysis was made of the relative size of actor and partner effects. For Husband, there is evidence for "couple model" (Kenny & Cook, 1999) in that the actor and partner effects are not statistically significantly different. It may make sense to sum or average the two Other Positivity scores for Husband. For Wife, there is evidence for "couple model" (Kenny & Cook, 1999) in that the actor and partner effects are not statistically significantly different. It may make sense to sum or average the two Other Positivity scores for Wife. not statistically significantly different. It may make sense to sum or average the two Other Positivity scores. Error Variances and Correlation The correlation between Husband errors with Wife errors is equal to .444. Thus, the two members of the dyad are similar to one another. The error variance for Husband is equal to .346 and for Wife is .323. The R squared (Kenny, Kashy, & Cook, 2006), controlling for the covariate, for the Husband is equal to .190 and for the Wife is equal to .212. Test of Distinguishability The test of distinguishability yields a chi square test with four degrees of freedom that equals 1.561 with a p value of .816. Because the test of distinguishability is not statistically significant, we conclude that members are statistically indistinguishable. The test of the effect of the distinguishing variable is not statistically significant (p = .620). The test of the interaction of the distinguishing variable with the actor effect is not statistically significant (p = .312), and the test interaction of the distinguishing variable with the partner effect is not statistically significant (p = .454). Finally, the test that error variances are different is not statistically significant (p = .632). Treating Dyad Members as Indistinguishable In the analyses that follow, we ignore differences between Husband and Wife. The overall actor effect is equal to .441 and is statistically significant (p < .001), with a medium effect size (beta = .340). The overall partner effect is equal to .313 and is statistically significant (p < .001), with a small effect size (beta = .242). The intraclass correlation treating dyad members as indistinguishable is equal to .448 and the R squared is equal to .323. Treating the dyad members as indistinguishable, there is evidence for "couple model" (Kenny & Cook, 1999) in that the actor and partner effects are The actor-partner interaction is equal to -.181 and is not statistically significant (p = .322). The partner effect for persons who are one standard deviation above the mean on Other Positivity is .224 and for persons who are one standard deviation below the mean on Other Positivity is .404. Alternatively, the effect of the absolute difference of the two members on Other Positivity is equal to -.073 and is not statistically significant (p = .527). Thus, if two members have the same score on Other Positivity, their score on Satisfaction is .073 units higher than it is for a dyad whose scores on Satisfaction differ by one unit. Treating dyad members as indistinguishable, there is not evidence of an actor-partner interaction. Table 1: Descriptive Statistics Variable Mean Standard Deviation ---------------------------------------------------------- Other Positivity Husband -.018 .523 Wife .018 .474 Satisfaction Husband 3.608 .656 Wife 3.588 .638 Table 2: Effect Estimates Effect Coefficient p value Beta ----------------------------------------------------------------- Actor (Husband) .374 <.001 .289 Actor (Wife) .523 <.001 .404 Partner (Wife to Husband) .372 <.001 .242 Partner (Husband to Wife) .261 .005 .201 Figure 1 APIM Diagram .374* Husband _________________________> Husband Other Positivity Satisfaction /\ \ /\ /\ / \ / \ ( \ / \ ( \ / \ ( \ / E1 ( \ / ) .055* [ X ] .149* ( / \ ) ( .372* / \ .261* E2 ( / \ / ( / \ / \ / \ / \/ / \/ \/ Wife .523* Wife Other Positivity _________________________> Satisfaction * p < .05 References Kenny, D. A., & Cook, W. (1999). Partner effects in relationship research: Conceptual issues, analytic difficulties, and illustrations. Personal Relationships, 6, 433-448. Kenny, D. A., Kashy, D. A., & Cook, W. (2006). Dyadic data analysis. New York: Guilford.