Key actor-actor and actor-partner effects: Given Affection and its Links to Value Consistent Behavior
Data Overview
Basic descriptives about key actor-parter variables
Between and Within Correlations, Taking into Account Nesting
these are the simple pooled correlations…e.g., average within and between. All correlations are significant, which means on average, actor affection is linked to partner valued action, with smallish average effect
| MPartnerYouShowAffection.wg | MPartnerYouActValueConsistent.wg | FPartnerYouShowAffection.wg | FPartnerYouActValueConsistent.wg | |
|---|---|---|---|---|
| MPartnerYouShowAffection.wg | 1.00 | 0.36 | 0.32 | 0.21 |
| MPartnerYouActValueConsistent.wg | 0.36 | 1.00 | 0.14 | 0.19 |
| FPartnerYouShowAffection.wg | 0.32 | 0.14 | 1.00 | 0.34 |
| FPartnerYouActValueConsistent.wg | 0.21 | 0.19 | 0.34 | 1.00 |
| MPartnerYouShowAffection.wg | MPartnerYouActValueConsistent.wg | FPartnerYouShowAffection.wg | FPartnerYouActValueConsistent.wg | |
|---|---|---|---|---|
| MPartnerYouShowAffection.wg | 0 | 0 | 0 | 0 |
| MPartnerYouActValueConsistent.wg | 0 | 0 | 0 | 0 |
| FPartnerYouShowAffection.wg | 0 | 0 | 0 | 0 |
| FPartnerYouActValueConsistent.wg | 0 | 0 | 0 | 0 |
| MPartnerYouShowAffection.bg | MPartnerYouActValueConsistent.bg | FPartnerYouShowAffection.bg | FPartnerYouActValueConsistent.bg | |
|---|---|---|---|---|
| MPartnerYouShowAffection.bg | 1.00 | 0.27 | 0.41 | 0.37 |
| MPartnerYouActValueConsistent.bg | 0.27 | 1.00 | 0.11 | 0.22 |
| FPartnerYouShowAffection.bg | 0.41 | 0.11 | 1.00 | 0.50 |
| FPartnerYouActValueConsistent.bg | 0.37 | 0.22 | 0.50 | 1.00 |
| MPartnerYouShowAffection.bg | MPartnerYouActValueConsistent.bg | FPartnerYouShowAffection.bg | FPartnerYouActValueConsistent.bg | |
|---|---|---|---|---|
| MPartnerYouShowAffection.bg | 0.00 | 0.02 | 0.00 | 0.00 |
| MPartnerYouActValueConsistent.bg | 0.02 | 0.00 | 0.34 | 0.06 |
| FPartnerYouShowAffection.bg | 0.00 | 0.34 | 0.00 | 0.00 |
| FPartnerYouActValueConsistent.bg | 0.00 | 0.06 | 0.00 | 0.00 |
I-ARIMAX
Here is where we run i-arimax (only run once as it is very time consuming)
We can see that whilst the pooled effects are significant, there is huge heterogeneity.
Caterpillar Plots
Here we visualize the heterogeneity. the blue bars show means. these means don’t describe many values.. for some tight link between affection and valued action for others little to no link
## <details><summary><b> MPartnerYouShowAffection_MPartnerYouActValueConsistent </b></summary>
## </details><br><details><summary><b> FPartnerYouShowAffection_MPartnerYouActValueConsistent </b></summary>
## </details><br><details><summary><b> MPartnerYouShowAffection_FPartnerYouActValueConsistent </b></summary>
## </details><br><details><summary><b> FPartnerYouShowAffection_FPartnerYouActValueConsistent </b></summary>
## </details><br>Cluster Identification
Visualization of Clusters identified by PAM (partitioning around medoids). second figure shows ideal number of clusters k = 2. Table shows means and sd of links between the indicated variables for cluster 1 (mean_1, sd_1) and cluster 2 (mean_2, sd_2). In cluster 1, all effects (actor-actor and actor-partner effects) seem to be higher than in cluster 2.
## [1] 0.2603858 0.2463347 0.1839885 0.2076782 0.2311024
## 20 23 51 1 12 16 17 18 19 22 24 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40
## 1 1 1 2 1 1 1 1 1 2 1 1 2 2 1 1 1 1 1 1 1 1 2 1 2 1
## 41 43 45 46 47 48 49 50 52 53 54 55 56 57 58 59 60 2 3 4 5 6 7 8 10 11
## 1 1 1 2 1 1 1 1 1 1 2 2 2 2 2 1 1 1 1 1 2 1 1 2 1 1
## 13 14 15
## 1 1 1## MPartnerYouShowAffection_predicts_MPartnerYouActValueConsistent_xreg
## 4 -0.009264995
## 39 0.556929144
## FPartnerYouShowAffection_predicts_MPartnerYouActValueConsistent_xreg
## 4 0.2321087
## 39 -1.0183252
## MPartnerYouShowAffection_predicts_FPartnerYouActValueConsistent_xreg
## 4 0.4266
## 39 -1.4711
## FPartnerYouShowAffection_predicts_FPartnerYouActValueConsistent_xreg
## 4 -0.1461535
## 39 -0.5828827
##
## 1 2
## 41 14mlVAR on Clusters
contemporaneous and lagged effects.
## Estimating temporal and between-subjects effects## | | | 0% | |================== | 25% | |=================================== | 50% | |==================================================== | 75% | |======================================================================| 100%## Estimating contemporaneous effects## | | | 0% | |================== | 25% | |=================================== | 50% | |==================================================== | 75% | |======================================================================| 100%## Computing random effects## | | | 0% | |=== | 4% | |====== | 8% | |======== | 12% | |=========== | 16% | |============== | 20% | |================= | 24% | |==================== | 28% | |====================== | 32% | |========================= | 36% | |============================ | 40% | |=============================== | 44% | |================================== | 48% | |==================================== | 52% | |======================================= | 56% | |========================================== | 60% | |============================================= | 64% | |================================================ | 68% | |================================================== | 72% | |===================================================== | 76% | |======================================================== | 80% | |=========================================================== | 84% | |============================================================== | 88% | |================================================================ | 92% | |=================================================================== | 96% | |======================================================================| 100%## Estimating temporal and between-subjects effects## | | | 0% | |================== | 25% | |=================================== | 50% | |==================================================== | 75% | |======================================================================| 100%## Estimating contemporaneous effects## | | | 0% | |================== | 25% | |=================================== | 50% | |==================================================== | 75% | |======================================================================| 100%## Computing random effects## | | | 0% | |========= | 12% | |================== | 25% | |========================== | 38% | |=================================== | 50% | |============================================ | 62% | |==================================================== | 75% | |============================================================= | 88% | |======================================================================| 100%##
## mlVAR estimation completed. Input was:
## - Variables: MPartnerYouShowAffection FPartnerYouShowAffection MPartnerYouActValueConsistent FPartnerYouActValueConsistent
## - Lags: 1
## - Estimator: lmer
## - Temporal: fixed
##
## Information indices:
## var aic bic
## MPartnerYouShowAffection 590.5773 626.1841
## FPartnerYouShowAffection 627.3928 662.9996
## MPartnerYouActValueConsistent 589.1498 624.7566
## FPartnerYouActValueConsistent 529.3748 564.9816
##
##
## Temporal effects:
## from to lag fixed SE
## MPartnerYouShowAffection MPartnerYouShowAffection 1 0.119 0.071
## MPartnerYouShowAffection FPartnerYouShowAffection 1 0.078 0.076
## MPartnerYouShowAffection MPartnerYouActValueConsistent 1 0.080 0.068
## MPartnerYouShowAffection FPartnerYouActValueConsistent 1 0.037 0.062
## FPartnerYouShowAffection MPartnerYouShowAffection 1 0.060 0.065
## FPartnerYouShowAffection FPartnerYouShowAffection 1 0.195 0.069
## FPartnerYouShowAffection MPartnerYouActValueConsistent 1 -0.005 0.063
## FPartnerYouShowAffection FPartnerYouActValueConsistent 1 -0.062 0.056
## MPartnerYouActValueConsistent MPartnerYouShowAffection 1 -0.026 0.069
## MPartnerYouActValueConsistent FPartnerYouShowAffection 1 -0.041 0.073
## MPartnerYouActValueConsistent MPartnerYouActValueConsistent 1 -0.083 0.066
## MPartnerYouActValueConsistent FPartnerYouActValueConsistent 1 0.042 0.060
## FPartnerYouActValueConsistent MPartnerYouShowAffection 1 0.082 0.066
## FPartnerYouActValueConsistent FPartnerYouShowAffection 1 0.071 0.070
## FPartnerYouActValueConsistent MPartnerYouActValueConsistent 1 0.020 0.063
## FPartnerYouActValueConsistent FPartnerYouActValueConsistent 1 0.132 0.057
## MPartnerYouShowAffection MPartnerYouShowAffection 1 0.119 0.071
## MPartnerYouShowAffection FPartnerYouShowAffection 1 0.078 0.076
## MPartnerYouShowAffection MPartnerYouActValueConsistent 1 0.080 0.068
## MPartnerYouShowAffection FPartnerYouActValueConsistent 1 0.037 0.062
## FPartnerYouShowAffection MPartnerYouShowAffection 1 0.060 0.065
## FPartnerYouShowAffection FPartnerYouShowAffection 1 0.195 0.069
## FPartnerYouShowAffection MPartnerYouActValueConsistent 1 -0.005 0.063
## FPartnerYouShowAffection FPartnerYouActValueConsistent 1 -0.062 0.056
## MPartnerYouActValueConsistent MPartnerYouShowAffection 1 -0.026 0.069
## MPartnerYouActValueConsistent FPartnerYouShowAffection 1 -0.041 0.073
## MPartnerYouActValueConsistent MPartnerYouActValueConsistent 1 -0.083 0.066
## MPartnerYouActValueConsistent FPartnerYouActValueConsistent 1 0.042 0.060
## FPartnerYouActValueConsistent MPartnerYouShowAffection 1 0.082 0.066
## FPartnerYouActValueConsistent FPartnerYouShowAffection 1 0.071 0.070
## FPartnerYouActValueConsistent MPartnerYouActValueConsistent 1 0.020 0.063
## FPartnerYouActValueConsistent FPartnerYouActValueConsistent 1 0.132 0.057
## P ran_SD
## 0.095 0
## 0.304 0
## 0.242 0
## 0.549 0
## 0.357 0
## 0.005 0
## 0.939 0
## 0.271 0
## 0.709 0
## 0.575 0
## 0.212 0
## 0.482 0
## 0.213 0
## 0.308 0
## 0.746 0
## 0.020 0
## 0.095 0
## 0.304 0
## 0.242 0
## 0.549 0
## 0.357 0
## 0.005 0
## 0.939 0
## 0.271 0
## 0.709 0
## 0.575 0
## 0.212 0
## 0.482 0
## 0.213 0
## 0.308 0
## 0.746 0
## 0.020 0
##
##
## Contemporaneous effects (posthoc estimated):
## v1 v2 P 1->2 P 1<-2
## FPartnerYouShowAffection MPartnerYouShowAffection 0.000 0.000
## MPartnerYouActValueConsistent MPartnerYouShowAffection 0.006 0.014
## MPartnerYouActValueConsistent FPartnerYouShowAffection 0.726 0.887
## FPartnerYouActValueConsistent MPartnerYouShowAffection 0.396 0.195
## FPartnerYouActValueConsistent FPartnerYouShowAffection 0.004 0.036
## FPartnerYouActValueConsistent MPartnerYouActValueConsistent 0.005 0.003
## pcor ran_SD_pcor cor ran_SD_cor
## 0.325 0.037 0.394 0.035
## 0.235 0.017 0.308 0.025
## 0.015 0.001 0.184 0.009
## 0.091 0.028 0.258 0.046
## 0.251 0.045 0.333 0.052
## 0.207 0.007 0.280 0.018
##
##
## Between-subject effects:
## v1 v2 P 1->2 P 1<-2
## FPartnerYouShowAffection MPartnerYouShowAffection 0.005 0.055
## MPartnerYouActValueConsistent MPartnerYouShowAffection 0.327 0.145
## MPartnerYouActValueConsistent FPartnerYouShowAffection 0.624 0.395
## FPartnerYouActValueConsistent MPartnerYouShowAffection 0.505 0.453
## FPartnerYouActValueConsistent FPartnerYouShowAffection 0.143 0.056
## FPartnerYouActValueConsistent MPartnerYouActValueConsistent 0.166 0.015
## pcor cor
## 0.407 0.540
## 0.225 0.403
## -0.017 0.308
## 0.127 0.437
## 0.323 0.494
## 0.370 0.494##
## mlVAR estimation completed. Input was:
## - Variables: MPartnerYouShowAffection FPartnerYouShowAffection MPartnerYouActValueConsistent FPartnerYouActValueConsistent
## - Lags: 1
## - Estimator: lmer
## - Temporal: fixed
##
## Information indices:
## var aic bic
## MPartnerYouShowAffection 166.76281 189.52947
## FPartnerYouShowAffection 155.92999 178.69665
## MPartnerYouActValueConsistent 36.83453 59.60119
## FPartnerYouActValueConsistent 148.78764 171.55430
##
##
## Temporal effects:
## from to lag fixed SE
## MPartnerYouShowAffection MPartnerYouShowAffection 1 0.201 0.107
## MPartnerYouShowAffection FPartnerYouShowAffection 1 -0.085 0.098
## MPartnerYouShowAffection MPartnerYouActValueConsistent 1 -0.006 0.037
## MPartnerYouShowAffection FPartnerYouActValueConsistent 1 -0.097 0.093
## FPartnerYouShowAffection MPartnerYouShowAffection 1 0.065 0.121
## FPartnerYouShowAffection FPartnerYouShowAffection 1 0.298 0.110
## FPartnerYouShowAffection MPartnerYouActValueConsistent 1 0.008 0.041
## FPartnerYouShowAffection FPartnerYouActValueConsistent 1 0.323 0.105
## MPartnerYouActValueConsistent MPartnerYouShowAffection 1 -0.067 0.298
## MPartnerYouActValueConsistent FPartnerYouShowAffection 1 0.262 0.274
## MPartnerYouActValueConsistent MPartnerYouActValueConsistent 1 -0.132 0.102
## MPartnerYouActValueConsistent FPartnerYouActValueConsistent 1 -0.008 0.260
## FPartnerYouActValueConsistent MPartnerYouShowAffection 1 -0.088 0.109
## FPartnerYouActValueConsistent FPartnerYouShowAffection 1 -0.016 0.100
## FPartnerYouActValueConsistent MPartnerYouActValueConsistent 1 -0.031 0.037
## FPartnerYouActValueConsistent FPartnerYouActValueConsistent 1 -0.171 0.095
## MPartnerYouShowAffection MPartnerYouShowAffection 1 0.201 0.107
## MPartnerYouShowAffection FPartnerYouShowAffection 1 -0.085 0.098
## MPartnerYouShowAffection MPartnerYouActValueConsistent 1 -0.006 0.037
## MPartnerYouShowAffection FPartnerYouActValueConsistent 1 -0.097 0.093
## FPartnerYouShowAffection MPartnerYouShowAffection 1 0.065 0.121
## FPartnerYouShowAffection FPartnerYouShowAffection 1 0.298 0.110
## FPartnerYouShowAffection MPartnerYouActValueConsistent 1 0.008 0.041
## FPartnerYouShowAffection FPartnerYouActValueConsistent 1 0.323 0.105
## MPartnerYouActValueConsistent MPartnerYouShowAffection 1 -0.067 0.298
## MPartnerYouActValueConsistent FPartnerYouShowAffection 1 0.262 0.274
## MPartnerYouActValueConsistent MPartnerYouActValueConsistent 1 -0.132 0.102
## MPartnerYouActValueConsistent FPartnerYouActValueConsistent 1 -0.008 0.260
## FPartnerYouActValueConsistent MPartnerYouShowAffection 1 -0.088 0.109
## FPartnerYouActValueConsistent FPartnerYouShowAffection 1 -0.016 0.100
## FPartnerYouActValueConsistent MPartnerYouActValueConsistent 1 -0.031 0.037
## FPartnerYouActValueConsistent FPartnerYouActValueConsistent 1 -0.171 0.095
## P ran_SD
## 0.061 0
## 0.388 0
## 0.878 0
## 0.301 0
## 0.591 0
## 0.007 0
## 0.837 0
## 0.002 0
## 0.822 0
## 0.339 0
## 0.194 0
## 0.975 0
## 0.417 0
## 0.876 0
## 0.412 0
## 0.073 0
## 0.061 0
## 0.388 0
## 0.878 0
## 0.301 0
## 0.591 0
## 0.007 0
## 0.837 0
## 0.002 0
## 0.822 0
## 0.339 0
## 0.194 0
## 0.975 0
## 0.417 0
## 0.876 0
## 0.412 0
## 0.073 0
##
##
## Contemporaneous effects (posthoc estimated):
## v1 v2 P 1->2 P 1<-2
## FPartnerYouShowAffection MPartnerYouShowAffection 0.106 0.146
## MPartnerYouActValueConsistent MPartnerYouShowAffection 0.681 0.929
## MPartnerYouActValueConsistent FPartnerYouShowAffection 0.632 0.775
## FPartnerYouActValueConsistent MPartnerYouShowAffection 0.549 0.517
## FPartnerYouActValueConsistent FPartnerYouShowAffection 0.036 0.027
## FPartnerYouActValueConsistent MPartnerYouActValueConsistent 0.151 0.123
## pcor ran_SD_pcor cor ran_SD_cor
## 0.221 0.014 0.249 0.016
## 0.046 0.035 0.087 0.045
## 0.046 0.001 0.146 0.016
## 0.022 0.015 0.117 0.032
## 0.312 0.009 0.348 0.019
## 0.234 0.024 0.269 0.041
##
##
## Between-subject effects:
## v1 v2 P 1->2 P 1<-2
## FPartnerYouShowAffection MPartnerYouShowAffection 0.095 0.180
## MPartnerYouActValueConsistent MPartnerYouShowAffection 0.406 0.807
## MPartnerYouActValueConsistent FPartnerYouShowAffection 0.095 0.032
## FPartnerYouActValueConsistent MPartnerYouShowAffection 0.796 0.218
## FPartnerYouActValueConsistent FPartnerYouShowAffection 0.586 0.001
## FPartnerYouActValueConsistent MPartnerYouActValueConsistent 0.439 0.040
## pcor cor
## 0.631 0.999
## 0.177 0.543
## -0.445 0.536
## 0.132 0.999
## 0.685 0.999
## 0.418 0.549Perceptual Agreement per Cluster
Table showing the mean and sd of Missed Cues ARIMAX outputs per Cluster (mean_1 -> Cluster 1).
Hypothesis 4 | Perceptual Agreement linked to Actor-Partner Effect
These are correlations between: idiographic ARIMAX effects of Actor Giving Affection x Partner Valued Behavior and idiographic ARIMAX effects of Actor Giving Affection x Partner Receiving Affection
Note that “Missed Cues” is a bit misleading here. The higher the ARIMAX effect between Given and Received Affection, the LOWER are Missed Cues. So we can see that the degree to which actors’ and partners’ perception of given and received affection agree correlate with the Affection x Valued Behavior links - but only for the Male-Female link!!!
ARIMAX Moderator Analysis
Cluster differences (covariates)
Covariates of Association Strength of Actor-Partner Links
These are meta-regressions for actor-actor and actor-partner links and covariates (note that: marital status 1 = unmarried, 2 = married).
Aggregated (Mean) Covariates and Trait-Level Affection and Valued Behavior
These are multiple regression models for trait-level Given Affection and Valued Behavior (aggregated per person, across time). Marital status 1 = unmarried, 2 = married. _z stands for standardized variables.
Covariate (Aggregated) and Missed Cues (Mean Difference Scores)
I aggregated all variables across timepoints per dyad. then ran linear regressions. missed cues was calculated as a difference score between given - received affection. so higher scores mean more missed cues. lower (or negative) scores mean less missed cues or even idealized (seen cues even though none were given). _z stands for standardized variables
##
## Call:
## lm(formula = sexual_activity_mean_z ~ M_missed_cues_mean_z +
## F_missed_cues_mean_z, data = final_df_clean)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.4294 -0.6451 -0.2164 0.4192 2.6083
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.07073 0.19438 0.364 0.719
## M_missed_cues_mean_z 0.13037 0.53665 0.243 0.810
## F_missed_cues_mean_z 0.63331 0.59762 1.060 0.298
##
## Residual standard error: 1.092 on 29 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.1262, Adjusted R-squared: 0.06594
## F-statistic: 2.094 on 2 and 29 DF, p-value: 0.1414##
## Call:
## lm(formula = RelateSatisfaction_z ~ M_missed_cues_mean_z + F_missed_cues_mean_z,
## data = final_df_clean)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.3862 -0.4080 0.2027 0.6018 1.1195
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.0449 0.1563 -0.287 0.7758
## M_missed_cues_mean_z -1.0898 0.4400 -2.477 0.0189 *
## F_missed_cues_mean_z -1.0245 0.4796 -2.136 0.0407 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9038 on 31 degrees of freedom
## Multiple R-squared: 0.1681, Adjusted R-squared: 0.1145
## F-statistic: 3.133 on 2 and 31 DF, p-value: 0.05767Covariates (ARIMAX)
To see not just how mean scores of covariates relate to other variables but look at each timepoint and each couple, I calculated ARIMAX for some more variable links. then, I ran t-test/ANOVA with previously identified clusters (giving affection x valued behavior) to see whether covariate links differ between clusters.