This note is concerned with the study of temporal development in several indices reflecting clustering effects in multilevel designs that are frequently utilized in educational and behavioral research. A latent variable method-based approach is outlined, which can be used to point and interval estimate the growth or decline in important functions…

Recent critiques of physics education research (PER) studies have revoiced the critical issues when drawing causal inferences from observational data where no intervention is present. In response to a call for a "causal reasoning primer" in PER, this paper discusses some of the fundamental issues in statistical causal inference. In…

Conventionally, regression discontinuity analysis contrasts a univariate regression's limits as its independent variable, "R," approaches a cut point, "c," from either side. Alternative methods target the average treatment effect in a small region around "c," at the cost of an assumption that treatment assignment,…

The central purpose of this article is to provide an overview of the many ways in which special educators can generate and think about causal inference to inform policy and practice. Consideration of causality across different lenses can be carried out by engaging in multiple method and mixed methods ways of thinking about inference. This article…

From the perspectives of the philosophy of science and statistical inference, we discuss the challenges of making prescriptive statements in quantitative research articles. We first consider the prescriptive nature of educational research and argue that prescriptive statements are a necessity in educational research. The logic of deduction,…

In the wake of an increasing political commitment to evidence-based decision making and evidence-based educational reform that emerged with the No Child Left Behind effort, the question of what counts as evidence has become increasingly important in the field of science education. In current public discussions, academics, politicians, and other…

Experimental data are analysed statistically to allow researchers to draw conclusions from a limited set of measurements. The hard fact is that researchers can never be certain that measurements from a sample will exactly reflect the properties of the entire group of possible candidates available to be studied (although using a sample is often the…

Beginning with a reference to living in a time of both uncertainty and opportunity, this article presents a discussion of key areas where shared understanding is needed if we are to successfully realize the design and use of high quality, valid assessments of science. The key areas discussed are: (1) assessment purpose and use, (2) the nature of…

Very little explanatory power is required in order for regressions to exhibit statistical significance. This article discusses some of the causes and implications. (Contains 2 tables.)

This paper advocates the use of nonparametric statistics. First, the consequence of using parametric inferential techniques under nonnormality is described. Second, the advantages of using nonparametric techniques are presented. The third purpose is to demonstrate empirically how infrequently nonparametric statistics appear in studies, even those…

Describes the logic of statistical testing in the Fisher and Neyman-Pearson approaches. Reviews some common misinterpretations of basic concepts behind statistical tests. Analyzes the philosophical and psychological issues that can contribute to these misinterpretations. Suggests possible ways in which statistical education might contribute to the…

Bootstrap analysis, both for nonparametric statistical inference and for describing sample results stability and replicability, has been gaining prominence among quantitative researchers in educational and psychological research. Procedurally, however, it is often quite a challenge for quantitative researchers to implement bootstrap analysis in…

This third in a series of articles on work conducted at the Texas Center for Educational Technology and the University of North Texas focuses on research designs for teachers to determine the impact of technology in the classroom. Highlights include research and the scientific method; qualitative versus quantitative research; and statistical…