Explore the vast range of titles available.

There has been a strong increase in the number of studies based on intensive longitudinal data, such as those obtained with experience sampling and daily diaries. These data contain a wealth of information regarding the dynamics of processes as they unfold within individuals over time. In this article, we discuss how combining intensive longitudinal data with either time-series analysis, which consists of modeling the temporal dependencies in the data for a single individual, or dynamic multilevel modeling, which consists of using a time-series model at Level 1 to describe the within-person process while allowing for individual differences in the parameters of these processes at Level 2, has led to new insights in clinical psychology. In addition, we discuss several methodological and statistical challenges that researchers face when they are interested in studying the dynamics of psychological processes using intensive longitudinal data.

Gendered trends in housework provide an important insight into changing gender inequality. In particular, they shed light on the debate over the stalling of the 'gender revolution'. Additionally, the gender division of housework is significantly related to couple well-being; disagreements over housework are among the major sources of marital conflict. The objective is to bring the evidence on gendered trends in time spent on core housework up to date, and to investigate cross-national variation in those trends. Using 66 time use surveys from 19 countries, we apply a random-intercept, random-slope model to investigate half a century of change in gender differences in housework (1961-2011). There is a general movement in the direction of greater gender equality, but with significant country differences in both the level and the pace of convergence. Specifically, there was a slowing of gender convergence from the late 1980s in those countries where men and women's time in housework was already more equal, with steeper gender convergence continuing in those countries where the gender division of housework was less equal. Our findings support the view that despite short-term stalls, slow-downs, and even reverses, as well as important differences in national policy contexts, the overall cross-national picture shows a continuing trend towards greater gender equality in the performance of housework.

Mediation analysis in repeated measures studies can shed light on the mechanisms through which experimental manipulations change the outcome variable. However, the literature on interval estimation for the indirect effect in the 1-1-1 single mediator model is sparse. Most simulation studies to date evaluating mediation analysis in multilevel data considered scenarios that do not match the expected numbers of level 1 and level 2 units typically encountered in experimental studies, and no study to date has compared resampling and Bayesian methods for constructing intervals for the indirect effect in this context. We conducted a simulation study to compare statistical properties of interval estimates of the indirect effect obtained using four bootstrap and two Bayesian methods in the 1-1-1 mediation model with and without random effects. Bayesian credibility intervals had coverage closest to the nominal value and no instances of excessive Type I error rates, but lower power than resampling methods. Findings indicated that the pattern of performance for resampling methods often depended on the presence of random effects. We provide suggestions for selecting an interval estimator for the indirect effect depending on the most important statistical property for a given study, as well as code in R for implementing all methods evaluated in the simulation study. Findings and code from this project will hopefully support the use of mediation analysis in experimental research with repeated measures.

Does collectivism influence an individual’s willingness to trust others? Conflicting empirical results from previous research and the role of trust in international marketing make this question important to resolve. The authors investigate this question across cultures and at the individual level with four studies using multiple methods. Study 1 establishes correlational evidence between societal-level collectivism and individual-level trust propensity with results from a multilevel analysis of data from over 6,000 respondents in 36 countries. Study 2 offers an individual-level analysis using the trust game, introducing a more rigorous behavioral outcome variable. Study 3 contributes causal evidence at the individual level based on experiments in both the United States and China and offers evidence of social projection as the explanatory mechanism. Finally, Study 4 demonstrates managerial relevance by using advertising to prime collectivism and assessing its effect on trust in the firm.

Interpersonal trust is associated with a range of adaptive outcomes, including knowledge sharing. However, to date, our knowledge of antecedents and consequences of employees feeling trusted by supervisors in organizations remains limited. On the basis of a multisource, multiwave field study among 956 employees from 5 Norwegian organizations, we examined the predictive roles of perceived mastery climate and employee felt trust for employees' knowledge sharing. Drawing on the achievement goal theory, we develop and test a model to demonstrate that when employees perceive a mastery climate, they are more likely to feel trusted by their supervisors at both the individual and group levels. Moreover, the relationship between employees' perceptions of a mastery climate and supervisor-rated knowledge sharing is mediated by perceptions of being trusted by the supervisor. Theoretical contributions and practical implications of our findings are discussed.

Extant research has established the effects of nostalgic brand positioning on brand equity, but studies have only examined individual nostalgic brand relationship dimensions separately. Combining these strands, we offer a holistic perspective of the mediating processes and identify contextual and firm-related moderators that affect the individual linkages. We draw on construal level theory and develop a multilevel model in which emotional attachment, brand local iconness, and brand authenticity explain how nostalgic brand positioning creates brand equity. We posit that country differences between emerging and developed markets and brand innovativeness moderate these mediating effects. The results from large consumer samples suggest that emotional attachment and brand local iconness play a weaker role in mediating the connection of nostalgic brand positioning and brand equity in emerging markets. However, this disadvantage in creating brand equity through nostalgic brand positioning in emerging markets can be attenuated with increasing levels of brand innovativeness.

We describe a web and standalone Shiny app for calculating the common, linear within-individual association for repeated assessments of paired measures with multiple individuals: repeated measures correlation (rmcorr). This tool makes rmcorr more widely accessible, providing a graphical interface for performing and visualizing the output of analysis with rmcorr. In contrast to rmcorr, most widely used correlation techniques assume paired data are independent. Incorrectly analyzing repeated measures data as independent will likely produce misleading results. Using aggregation or separate models to address the issue of independence may obscure meaningful patterns and will also tend to reduce statistical power. rmcorrShiny (repeated measures correlation Shiny) provides a simple and accessible solution for computing the repeated measures correlation. It is available at: https://lmarusich.shinyapps.io/shiny_rmcorr/.

Context effects, where a characteristic of an upper-level unit or cluster (e.g., a country) affects outcomes and relationships at a lower level (e.g., that of the individual), are a primary object of sociological inquiry. In recent years, sociologists have increasingly analyzed such effects using quantitative multilevel modeling. Our review of multilevel studies in leading sociology journals shows that most assume the effects of lower-level control variables to be invariant across clusters, an assumption that is often implausible. Comparing mixed-effects (random-intercept and slope) models, cluster-robust pooled OLS, and two-step approaches, we find that erroneously assuming invariant coefficients reduces the precision of estimated context effects. Semi-formal reasoning and Monte Carlo simulations indicate that loss of precision is largest when there is pronounced cross-cluster heterogeneity in the magnitude of coefficients, when there are marked compositional differences among clusters, and when the number of clusters is small. Although these findings suggest that practitioners should fit more flexible models, illustrative analyses of European Social Survey data indicate that maximally flexible mixed-effects models do not perform well in real-life settings. We discuss the need to balance parsimony and flexibility, and we demonstrate the encouraging performance of one prominent approach for reducing model complexity.

Interruption of work by e-mail and other communication technologies has become widespread and ubiquitous. However, our understanding of how such interruptions influence individual performance is limited. This paper distinguishes between two types of e-mail interruptions (incongruent and congruent) and draws upon action regulation theory and the computer-mediated communication literature to examine their direct and indirect effects on individual performance. Two empirical studies of sales professionals were conducted spanning different time frames: a survey study with 365 respondents and a diary study with 212 respondents. The results were consistent across the two studies, showing a negative indirect effect of exposure to incongruent interruptions (interruptions containing information that is not relevant to primary activities) through subjective workload, and a positive indirect effect of exposure to congruent interruptions (interruptions containing information that is relevant to primary activities) through mindfulness. The results differed across the two studies in terms of whether the effects were fully or partially mediated, and we discuss these differences using meta-inferences. Technology capabilities used during interruption episodes also had significant effects: rehearsing (fine-tuning responses to incoming messages) and reprocessing (reexamining received messages) were positively related to mindfulness, parallel communication (engaging in multiple e-mail conversations simultaneously) and leaving messages in the inbox were positively related to subjective workload, and deleting messages was negatively related to subjective workload. This study contributes to research by providing insights on the different paths that link e-mail interruptions to individual performance and by examining the effects of using capabilities of the interrupting technology (IT artifact) during interruption episodes. It also complements the experimental tradition that focuses on isolated interruptions. By shifting the level of analysis from specific interruption events to overall exposure to interruptions over time and from the laboratory to the workplace, our study provides realism and ecological validity.