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Psychological research has increasingly recognized the importance of integrating temporal dynamics into its theories, and innovations in longitudinal designs and analyses have allowed such theories to be formalized and tested. However, psychological researchers may be relatively unequipped to analyze such data, given its many characteristics and the general complexities involved in longitudinal modeling. The current paper introduces time series analysis to psychological research, an analytic domain that has been essential for understanding and predicting the behavior of variables across many diverse fields. First, the characteristics of time series data are discussed. Second, different time series modeling techniques are surveyed that can address various topics of interest to psychological researchers, including describing the pattern of change in a variable, modeling seasonal effects, assessing the immediate and long-term impact of a salient event, and forecasting future values. To illustrate these methods, an illustrative example based on online job search behavior is used throughout the paper, and a software tutorial in R for these analyses is provided in the Supplementary Materials.

Using representative cross-sections from 166 nations (more than 1.7 million respondents), we examined differences in three measures of subjective well-being over the life span. Globally, and in the individual regions of the world, we found only very small differences in life satisfaction and negative affect. By contrast, decreases in positive affect were larger. We then examined four important predictors of subjective well-being and how their associations changed: marriage, employment, prosociality, and life meaning. These predictors were typically associated with higher subjective well-being over the life span in every world region. Marriage showed only very small associations for the three outcomes, whereas employment had larger effects that peaked around age 50 years. Prosociality had practically significant associations only with positive affect, and life meaning had strong, consistent associations with all subjective-well-being measures across regions and ages. These findings enhance our understanding of subjective-well-being patterns and what matters for subjective well-being across the life span.

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Developing self-report Likert scales is an essential part of modern psychology. However, it is hard for psychologists to remain apprised of best practices as methodological developments accumulate. To address this, this current paper offers a selective review of advances in Likert scale development that have occurred over the past 25 years. We reviewed six major measurement journals (e.g., Psychological Methods, Educational, and Psychological Measurement) between the years 1995–2019 and identified key advances, ultimately including 40 papers and offering written summaries of each. We supplemented this review with an in-depth discussion of five particular advances: (1) conceptions of construct validity, (2) creating better construct definitions, (3) readability tests for generating items, (4) alternative measures of precision [e.g., coefficient omega and item response theory (IRT) information], and (5) ant colony optimization (ACO) for creating short forms. The Supplementary Material provides further technical details on these advances and offers guidance on software implementation. This paper is intended to be a resource for psychological researchers to be informed about more recent psychometric progress in Likert scale creation.