WARNINGS: 1. With covariates, ApimDText can fail to remove missing cases on the covariates. The researcher should remove those cases before undertaking the analysis. 2. Because zero is not a possible value for Other Positivity, grand-mean centering that variable should be considered.
Actor-Partner Interdependence Model for Wives and Husbands
The focus of this study is the investigation of the effect of Other Positivity on Satisfaction and how that effect differs for Wives and Husbands. Both the effect of own Other Positivity (actor) and the effect of partner's Other Positivity (partner) on Satisfaction for Wives and Husbands are studied. There are a total of 148 dyads with no missing data. The total number of individuals is 296. The means and standard deviations for Wives and Husbands 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 (.006 proportion of the total variance for the Wives and .016 proportion for the Husbands), chi square test with 1 degree of freedom equal to 9.849 (p = .002).
RESULTS
Actor Effects
The actor effect for Wives is equal to .384 and is statistically significant (p < .001), with a medium effect size (beta = .386), and the actor effect for Husbands is equal to .442 and is statistically significant (p < .001), with a medium effect size (beta = .443). (See Table 2 for the actor effect estimates.) The difference between these two actor effects is not statistically significant (p = .584).
Partner Effects
The partner effect from Husbands to Wives is equal to .339 and is statistically significant (p < .001), with a medium effect size (beta = .340). The partner effect from Wives to Husbands is equal to .268 and is statistically significant (p < .001), with a small effect size (beta = .269). (See Table 2 for the partner effect estimates.) The difference between these two partner effects is not statistically significant (p = .508).
Actor-Partner Interactions
The effect of the product of actor and partner variables on Satisfaction for Wives is equal to -.150 and is not statistically significant (p = .367). The partner effect for persons who are one standard deviation above the mean on Other Positivity is .258 and for persons who are one standard deviation below the mean on Other Positivity is .414. Additionally, the effect of the product of actor and partner variables on Satisfaction for Husbands is equal to -.356 and is statistically significant (p = .010). The partner effect for persons who are one standard deviation above the mean on Other Positivity is .101 and for persons who are one standard deviation below the mean on Other Positivity is .438. The difference between the interaction effects for Wives and Husbands is not statistically significant (p = .179).
The effect of the absolute difference of the two members' scores for the variable Other Positivity on Satisfaction of Wives is equal to -.040 and is not statistically significant (p = .711). Thus, if two members have the same score on Other Positivity, the score on Satisfaction for Wives is .040 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' scores for the variable Other Positivity on Satisfaction of Husbands is equal to .022 and is not statistically significant (p = .802). Thus, if two members have the same score on Other Positivity, their score on Satisfaction for Husbands is .022 units lower 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 = .540).
Effect of the Distinguishing Variable
The predicted score on Satisfaction for those who score zero on Other Positivity is .510 and .590 for Husbands, and that difference is not statistically significant (p = .840), with a small effect size (d = -.190).
Relation of Actor and Partner Effects: Testing for Patterns
An analysis was made of the relative size of actor and partner effects to determine if there were any patterns in the effects. For Wives, 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 Wives. For Husbands, 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 Husbands.
Error Variances and Correlations
The correlation between Wives errors with Husbands errors is equal to .470. Thus, the two members of the dyad are similar to one another. The error variance for Wives is equal to .206 and for Husbands is .141. The R squared (Kenny, Kashy, & Cook, 2006), controlling for the covariate, for the Wives is equal to .269 and for the Husbands is equal to .343. Finally, the correlation between Other Positivity for Wives and Husbands is equal to .224.
Test of Distinguishability
The test of distinguishability yields a chi square test with four degrees of freedom that equals 7.786 (p = .100). 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 = .840). The test of the interaction of the distinguishing variable with the actor effect is not statistically significant (p = .584), and the test interaction of the distinguishing variable with the partner effect is not statistically significant (p = .508). Finally, the test that error variances are different is statistically significant (p = .009).
Treating Dyad Members as Indistinguishable
In the analyses that follow, we ignore differences between Wives and Husbands. The overall actor effect is equal to .411 and is statistically significant (p < .001), with a medium effect size (beta = .413). The overall partner effect is equal to .299 and is statistically significant (p < .001), with a small effect size (beta = .300). The intraclass correlation treating dyad members as indistinguishable is equal to .465 and the R squared is equal to .141. Treating the dyad members as indistinguishable, 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.
The actor-partner interaction is equal to -.256 and is not statistically significant (p = .052). The partner effect for persons who are one standard deviation above the mean on Other Positivity is .172 and for persons who are one standard deviation below the mean on Other Positivity is .427. Alternatively, the effect of the absolute difference of the two members on Other Positivity is equal to -.003 and is not statistically significant (p = .975). Thus, if two members have the same score on Other Positivity, their score on Satisfaction is .003 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
Wives 4.246 .523
Husbands 4.281 .474
Satisfaction
Wives 3.591 .530
Husbands 3.618 .462
Table 2: Effect Estimates
Effect Coefficient p value Beta
----------------------------------------------------------------
Actor (Wives) .384 <.001 .386
Actor (Husbands) .442 <.001 .443
Partner (Husbands to Wives) .339 <.001 .340
Partner (Wives to Husbands) .268 <.001 .269
Figure 1
APIM Diagram (unstandardized estimates)
.384*
Wives _________________________> Wives
Other Positivity Satisfaction
/\ \ /\ /\
/ \ / \
( \ / \
( \ / \
( \ / E1
( \ / )
.055* [ X ] .080*
( / \ )
( .339* / \ .268* E2
( / \ /
( / \ /
\ / \ /
\/ / \/ \/
Husbands .442* Husbands
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.