Fig 1.
Linear regression model to predict RQ using personality variables.
Different RQ measures on the right were predicted by different sets of personality scores on the left. CC: Combination Counts. RQ: Relationship Quality.
Table 1.
Operationalization of personality variables at T1 with content domains.
Table 2.
Self-assessed aspects of RQ measures.
Fig 2.
The figure depicts the exclusion criteria and the number of participants affected by each (if not already excluded for a preceding reason).
Participant flow. The figure shows that the main data source of the 192 partners used in the current study were the 120 partners who took part in the Stern study as well as in the follow-up four years later. The included study subjects are marked in grey. No information on the drop-out due to starting but not finishing the T1 surveys could be found.
Table 3.
Descriptive statistics about RQ (n = 192 for T2).
Table 4.
10*10-fold CV performance of the elastic net models based on different variable sets (n = 192).
Fig 3.
Actual vs. predicted RQ overall for one of the 10 CV iterations based on all actor, partner and similarity variables.
Since only the values of one of 10 CV iterations are presented—not the average of all CV iterations: the shown r2 and MSE values differ from the performance reported in Table 2. The figure shows that the actual and the predicted outcome are correlated—with the model predicting more accurately on higher values of actual RQ.
Table 5.
Study evaluation.