Dynamic structural equation modeling (DSEM) is a useful technique for analyzing intensive longitudinal data. A challenge of applying DSEM is the missing data problem. The impact of missing data on DSEM, especially on widely applied DSEM such as the two-level vector autoregressive (VAR) cross-lagged models, however, is understudied. To fill the…

Conducting research among hard-to-reach populations is a difficult endeavor because some of their characteristics are known to be associated with survey nonresponse and panel attrition. In the case of the Parchemins study, which followed undocumented migrants over their process of regularization and during the first years of regularized life in…

Managing and analysing large qualitative datasets pose a particular challenge for researchers seeking a consistent and rigorous approach to qualitative data analysis. This paper describes and demonstrates the development and adoption of a matrix tool to guide the qualitative data analysis of a large sample (N = 122) of interview data. The paper…

The Monitoring the Future (MTF) study monitors historical and developmental changes in substance use prevalence among key subgroups of the general U.S. adolescent and adult population. The current study first devised and evaluated a cohort-specific pooled analysis weighing procedure for the MTF panel study that weighted back to the initial 12th…

This article analyzes whether response patterns in surveys differ between the general population, regular immigrants, and recent refugees. Analyses show that the address quality of refugees contacted in the first wave of a panel study is worse than that of the general population, but of a similar quality to that of other recent immigrants. Once…

During the COVID19 crisis, school closure was a frequent feature of Government responses. "The Children's School Lives" (CSL) national cohort study of primary schooling in Ireland had to be adapted and transferred online as an interim response to the unprecedented impact that the pandemic had on the research environment. Adapting…

Intensive longitudinal data is increasingly used to study state-like processes such as changes in daily stress. Measures aimed at collecting such data require the same level of scrutiny regarding scale reliability as traditional questionnaires. The most prevalent methods used to assess reliability of intensive longitudinal measures are based on…

Statewide longitudinal data systems (SLDSs) can enable researchers, policymakers, and practitioners to identify and understand important relationships and trends across the education-to-workforce continuum. A well-developed SLDS can increase state and territory governments' ability to establish more informed and equitable policies, enable agency…

Passive data from a tracking application (or "meter") installed on participants' devices to register the URLs visited have great potential for studying people's online activities. However, given privacy concerns, obtaining cooperation installing a meter can be difficult and lead to selection bias. Therefore, in this article, we address…

Increasingly surveys are using interviewers to collect objective health measures, also known as biomeasures, to replace or supplement traditional self-reported health measures. However, the extent to which interviewers affect the (im)precision of biomeasurements is largely unknown. This article investigates interviewer effects on several…

Collecting biological data in representative surveys is becoming more common due to their potential to inform research and policy. Nevertheless, using nurses to collect these data can lead to unintended effects. In this paper, we investigate how nurses influence the non-response process by looking at five waves of data coming from two surveys in…

In this article, we explore the use of Facebook targeted advertisements for the collection of survey data. We illustrate the potential of survey sampling and recruitment on Facebook through the example of building a large employee--employer linked data set as part of The Shift Project. We describe the workflow process of targeting, creating, and…

Introduction: Planned missing designs are relatively new to the field of psychological and developmental research. These designs allow researchers to randomly assign participants to missing data conditions; participants are either randomly selected to receive or not receive particular measures or items during data collection (Little &…

Technical documentation for educational tests focuses primarily on properties of individual scores at single points in time. Reliability, standard errors of measurement, item parameter estimates, fit statistics, and linking constants are standard technical features that external stakeholders use to evaluate items and individual scale scores.…

Large-scale assessment survey (LSAS) data are collected via complex sampling designs with special features (e.g., clustering and unequal probability of selection). Multilevel models have been utilized to account for clustering effects whereas the probability weighting approach (PWA) has been used to deal with design informativeness derived from…