Discrete-time survival analysis (DTSA) models are a popular way of modeling events in the social sciences. However, the analysis of discrete-time survival data is challenged by missing data in one or more covariates. Negative consequences of missing covariate data include efficiency losses and possible bias. A popular approach to circumventing…

Multiple imputation (MI) is a popular method for handling missing data. In education research, it can be challenging to use MI because the data often have a clustered structure that need to be accommodated during MI. Although much research has considered applications of MI in hierarchical data, little is known about its use in cross-classified…

Although the null hypothesis significance testing procedure is problematic, many still favor the use of "p"-values as indicating the state of evidence against the model used to generate the "p"-value. From this perspective, "p"-values benefit science; or would benefit science if used correctly. In contrast, the novel…

This article addresses the problem of estimating the proportion Pi[subscript S] of the population belonging to a sensitive group using optional randomized response technique in stratified sampling based on Mangat model that has proportional and Neyman allocation and larger gain in efficiency. Numerically, it is found that the suggested model is…

In this paper, we investigate two purported problems with Bayesian Knowledge Tracing (BKT), a popular statistical model of student learning: "identifiability" and "semantic model degeneracy." In 2007, Beck and Chang stated that BKT is susceptible to an "identifiability problem"--various models with different…

Age-period-cohort (APC) models are designed to estimate the independent effects of age, time periods, and cohort membership. However, APC models suffer from an identification problem: There are no unique estimates of the independent effects that fit the data best because of the exact linear dependency among age, period, and cohort. Among methods…

In education research, small samples are common because of financial limitations, logistical challenges, or exploratory studies. With small samples, statistical principles on which researchers rely do not hold, leading to trust issues with model estimates and possible replication issues when scaling up. Researchers are generally aware of such…

We offer an introduction to the five papers that make up this special section. These papers deal with a range of the methodological challenges that face researchers analyzing fMRI data--the spatial, multilevel, and longitudinal nature of the data, the sources of noise, and so on. The papers all provide analyses of data collected by a multi-site…

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…

Debate is occurring about which result interpretation aides focused on examining the experimental effect should be used in single-subject experimental research. In this study, we examined seven nonoverlap methods and compared results using each method to judgments of two visual analysts. The data sources for the present study were 36 studies…

Wayfinding is a kind of spatial riddle that people encounter almost daily. Although it has been well documented that wayfinding elements--namely, environmental cues, people and time--significantly influence wayfinding, there has been little work done to examine the effectiveness of those influences. In particular, the notion of wayfindingly…

Education research rarely lends itself to large scale experimental research and true randomization, leaving the researcher to quasi-experimental designs. The problem with quasi-experimental research is that underlying factors may impact group selection and lead to potentially biased results. One way to minimize the impact of non-randomization is…

Notes that family researchers can examine extent of self-selection bias in samples by using range of "plausibly correlated characteristics" such as marriage and divorce public records. Provides extensive case example of analyses and discusses compensation techniques of weighting and hazard rate models. (Author/NB)

Per definition, CSCL research deals with the data of individuals nested in groups, and the influence of a specific learning setting on the collaborative process of learning. Most well-established statistical methods are not able to analyze such nested data adequately. This article describes the problems which arise when standard methods are…

The epistemological status of factors--that is, components, common factors, and image factors--is briefly discussed. Implications for the number of factors problem of varying views of factor analysis and the particular factor analytic model employed are noted, and the rationales underlying the best known decision rules regarding the correct number…