Single subject (SS) designs are popular in educational and psychological research. There exist several statistical techniques designed to analyze such data and to address the question of whether an intervention has the desired impact. Recently, researchers have suggested that generalized additive models (GAMs) might be useful for modeling…

Mediation is a causal process that evolves over time. Thus, a study of mediation requires data collected throughout the process. However, most applications of mediation analysis use cross-sectional rather than longitudinal data. Another implicit assumption commonly made in longitudinal designs for mediation analysis is that the same mediation…

This research empirically evaluates data sets from the National Center for Education Statistics (NCES) for design effects of ignoring the sampling design in weighted two-level analyses. Currently, researchers may ignore the sampling design beyond the levels that they model which might result in incorrect inferences regarding hypotheses due to…

"Growth mixture models" (GMMs) with nonignorable missing data have drawn increasing attention in research communities but have not been fully studied. The goal of this article is to propose and to evaluate a Bayesian method to estimate the GMMs with latent class dependent missing data. An extended GMM is first presented in which class…

Perfectionistic concerns (i.e., negative reactions to failures, concerns over others' criticism and expectations, and nagging self-doubts) are a putative risk factor for depressive symptoms. This study proposes and supports the existential model of perfectionism and depressive symptoms (EMPDS), a conceptual model aimed at explaining why…

The modeling of longitudinal and multilevel data using a latent variable framework is reviewed. Particular emphasis is placed on growth modeling. Examples are discussed where repeated observations are made on students sampled within classrooms and schools. The concept of a latent variable is a convenient way to represent statistical variation not…

Sources of population heterogeneity may or may not be observed. If the sources of heterogeneity are observed (e.g., gender), the sample can be split into groups and the data analyzed with methods for multiple groups. If the sources of population heterogeneity are unobserved, the data can be analyzed with latent class models. Factor mixture models…

Research design sampling models regarding educational research of within-grade influences on overall educational experiences are discussed and limitations of each model noted. (DEP)

In the direct and indirect effects of teacher characteristics on educational production of students over time, this study indicates that teacher characteristics were not critical determinants of student achievement. Characteristics include: experience, educational level, recentness of degree and degree nature, college quality, and other…

This study explored the assumption that the percentile rank of a group of students should be expected to remain the same on a post-test as on a pretest when the treatment of the group in the intervening period was the same as the treatment of the norms population. This assumption is basic to the use of the norm-referenced model for the assessment…

Activities involved in the collection and assembling of data for computer processing from the first followup survey of the National Longitudinal Study of the High School Class of 1972 (NLS) are briefly described. Included are an overview of the NLS; the sample design and survey participation; the development of the first followup survey…

One of the largest investigations of elementary education ever undertaken, the Sustaining Effects Study sought answers to a series of policy questions. The two major issues addressed by the study were (1) Who receives compensatory education (CE)? and (2) How effective is CE? Related to these primary issues were a number of secondary questions: (3)…