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Despite a large body of empirical literature on sexual satisfaction, its development over the course of a relationship is still unclear. Only a small number of studies, most of which have relied on cross-sectional data of convenience samples, have explicitly focused on relationship duration, and empirical evidence is mixed. We analyzed how sexual satisfaction changes over the course of a relationship using three waves of the German Family Panel study (pairfam). We concentrated our analyses on young and middle-aged heterosexual individuals in committed relationships (N = 2,814) and applied fixed effects regression models, which have the advantage of estimations based on changes within individuals over time. We found a positive development of sexual satisfaction in the first year of a relationship, followed by a steady decline. This pattern persisted even when controlling for the frequency of intercourse, although the effects were, in part, mediated by intercourse frequency. We explained the non-linear effect of relationship duration on sexual satisfaction with an initial learning effect regarding partner-specific sexual skills, which is then outweighed by a decline in passion at later stages of a relationship. Moreover, we found significant effects for the control variables of health status, intimacy in couple communication, and conflict style, as expected. In contrast to past research, however, cohabitation and marriage were not found to play a role for sexual satisfaction in our data. Further research is required to deepen the understanding of the reasons why sexual satisfaction changes with relationship duration.

Cluster policy is increasingly becoming part of many governments’ economic policy strategies. At the same time, evidence-based policy-making is gaining importance, bringing about a call for policy evaluation. Since the quality of the evaluation results depends highly on the method used, data, assumptions and techniques must be adequate for the specific evaluation question. This holds for cluster policy evaluation in particular, given the complexity and indirect nature of cluster policy interventions. This article provides an overview of evaluation methods suited to the ex-post analysis of cluster policy, covering both micro- and macroeconomic approaches.

This study explores how researchers’ analytical choices affect the reliability of scientific findings. Most discussions of reliability problems in science focus on systematic biases. We broaden the lens to emphasize the idiosyncrasy of conscious and unconscious decisions that researchers make during data analysis. We coordinated 161 researchers in 73 research teams and observed their research decisions as they used the same data to independently test the same prominent social science hypothesis: that greater immigration reduces support for social policies among the public. In this typical case of social science research, research teams reported both widely diverging numerical findings and substantive conclusions despite identical start conditions. Researchers’ expertise, prior beliefs, and expectations barely predict the wide variation in research outcomes. More than 95% of the total variance in numerical results remains unexplained even after qualitative coding of all identifiable decisions in each team’s workflow. This reveals a universe of uncertainty that remains hidden when considering a single study in isolation. The idiosyncratic nature of how researchers’ results and conclusions varied is a previously underappreciated explanation for why many scientific hypotheses remain contested. These results call for greater epistemic humility and clarity in reporting scientific findings.

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