Imputation or likelihood-based approaches to handle missing data assume the data are missing completely at random (MCAR) or missing at random (MAR). However, little research has examined the missingness pattern before using these imputation/likelihood methods. Three missingness mechanisms -- MCAR, MAR, and not missing at random (NMAR) -- can be…

Nonresponse bias is a widely prevalent problem for data on education. We develop a ten-step exemplar to guide nonresponse bias analysis (NRBA) in cross-sectional studies and apply these steps to the Early Childhood Longitudinal Study, Kindergarten Class of 2010-2011. A key step is the construction of indices of nonresponse bias based on proxy…

Panel data methods, which include difference-in-differences and comparative interrupted time series, have become increasingly common in education policy research. The key idea is to use variation across time and space (e.g., school districts) to estimate the effects of policy or programmatic changes that happen in some localities but not others.…

Panel data methods, which include difference-in-differences and comparative interrupted time series, have become increasingly com- mon in education policy research. The key idea is to use variation across time and space (e.g., school districts) to estimate the effects of policy or programmatic changes that happen in some localities but not others.…

This case study provides an account of my experiences and lessons learned in designing and implementing a survey research. The research was part of my doctoral thesis in educational measurement and quantitative methods. The purpose of the study was to examine the effectiveness of a Completely Structured Training compared with Partially Structured…

"What works" policies are the latest incarnation of best practices in educational research. Instituted by various organisations internationally, they define what kind of research counts as "evidence" for reform-oriented decision-making. While some countries rely on systematic analyses and meta-analyses, the U.S. favours primary…

The purpose of this article is to inform researchers about and encourage the use of longitudinal designs to further understanding of human resource development and organizational theory. This article presents information about a variety of longitudinal research designs, related statistical procedures, and an overview of general data collecting…

We examine the performance of planned missing (PM) designs for correlated latent growth curve models. Using simulated data from a model where latent growth curves are fitted to two constructs over five time points, we apply three kinds of planned missingness. The first is item-level planned missingness using a three-form design at each wave such…

Quantitative research in vocational education and training (VET) is routinely affected by missing or incomplete information. However, the handling of missing data in published VET research is often sub-optimal, leading to a real risk of generating results that can range from being slightly biased to being plain wrong. Given that the growing…

In this article, the author discusses how researchers can use mixed-methods approaches and intersectional analyses to understand college access among first-generation Asian American and Pacific Islanders (AAPIs). First, he discusses the utility of mixed-methods approaches and intersectionality research in studying college access. Then, he…

Developmental science rests on describing, explaining, and optimizing intraindividual changes and, hence, empirically requires longitudinal research. Problems of missing data arise in most longitudinal studies, thus creating challenges for interpreting the substance and structure of intraindividual change. Using a sample of reports of longitudinal…

This paper introduces an empirical strategy to estimate dynamic treatment effects in randomized trials that provide treatment in multiple stages and in which various noncompliance problems arise such as attrition and selective transitions between treatment and control groups. Our approach is applied to the highly influential four year randomized…

Simple Markov models are fitted to a small sample of longitudinal categorical data of teachers' ratings of children's classroom behavior. Although the data consist only of observations at five occasions, it was possible, after dividing the data into two groups, to fit plausible models in continuous time. (Author/BW)

Used statistical procedures that have become routine in other social sciences to analyze data from clinical service records. Despite absence of control groups, nonrandom assignment of clients to treatment conditions, and incomplete records, effective analyses of psychotherapeutic process were possible. Graphical methods for summarizing large data…

Challenges the typical treatment of causal effects in longitudinal data, arguing that models should be conceptualized and tested in ways that directly reflect prior assumptions as to the trait- or state-like nature of the variables. Examples demonstrate that meaningful longitudinal studies of state variables can be conducted without assuming their…