with GMC_{ESM} = grand-mean centered on the ESM-mean,i = person-specific index, j = couple-specific index, ? = fixed effect, (z) =z-standardized, u = random intercept,r = error term. This translates into the following between-person interpretation of the estimates:

For all models, we report the marginal R 2 as an effect size, representing the explained variance by the fixed effects (R 2 _{GLMM(m)} from the MuMIn package, Johnson, 2014; Barton, 2018; Nakagawa Schielzeth, 2013). When making multiple tests for a single analysis question (i.e., due to multiple items, summary statistics, moderators), we controlled the false discovery rate (FDR) at? = 5% (two-tailed) with the Benjamini-Hochberg (BH) correction of the p-values (Benjamini Hochberg, 1995) implemented in thestats package (R Core Team, 2018). 10

## Outcome of One another Studies

Table 2 suggests the latest detailed statistics both for education. Correlations and you may a complete breakdown of one’s factor prices, rely on times, and you may feeling sizes for everyone show are in the latest Supplemental Content.

Desk 3 suggests the fresh standard regression coefficients for a few ESM summation statistics anticipating retrospection immediately after 2 weeks (Investigation step one) and you can a month (Investigation dos) out-of ESM, on their own on the additional matchmaking satisfaction activities. Both for training and all issues, the best anticipate is accomplished by new imply of your entire analysis period, as the indicate of one’s history big date therefore the 90th quantile of the shipment did the newest worst. Complete, the greatest connections had been found into imply of the measure of all around three ESM circumstances anticipating the size of all the about three retrospective examination (? = 0.75), and for the indicate out-of you want satisfaction forecasting retrospection with the goods (? = 0.74).

## Items step one = Dating vibe, Item 2 = Annoyance (contrary coded), Goods step three = You need pleasure

Letterote: Letter (Data step one) = 115–130, Letter (Investigation dos) = 475–510. CSI = Lovers Pleasure List reviewed till the ESM several months. Rows purchased because of the sized mediocre coefficient round the all of the circumstances. The strongest effect is written in committed.

The same analysis for the prediction of a global relationship satisfaction measure (the CSI) instead of the retrospective assessment is also shown in Table3 (for the prediction of PRQ and NRQ see Supplemental Materials). The mean of the last week, of the last day and of the first week were not entered as predictors, as they provide no special meaning to the global evaluation, which was assessed before the ESM part. Again, the mean was the best predictor in all cases. Other summary statistics performed equally well in some cases, but without a systematic pattern. The associations were highest when the mean of the scale, or the mean of need satisfaction (item 3) across four weeks predicted the CSI (?_{Size} = 0.59, ?_{NeedSatisfaction} = 0.58).

We additionally checked whether other summary statistics next to the mean provided an incremental contribution to the prediction of retrospection (see Table 4). This was not the case in Study 1 (we controlled the FDR for all incremental effects across studies, all BH-corrected ps of the model comparisons >0.16). In Study 2, all summary statistics except the 90th quantile and the mean of the first week made incremental contributions for the prediction of retrospection of relationship mood and the scale. For the annoyance item both the 10th and the 90th quantile – but no other summary statistic – had incremental effects. As annoyance was reverse coded, the 10th quantile represents a high level of annoyance, whereas the 90th quantile represents a low level of annoyance. For need satisfaction only the summaries of the end of the study (i.e., mean of the last week and mean of the last day) had additional relevance. Overall the incremental contributions were small (additional explained variance <3%, compared to baseline explained variance of the mean as single predictor between 30% and 57%). Whereas the coefficients of the 10th quantile and the means of the last day/week were positive, the median and the 90th quantile had negative coefficients.