Publication bias distorts the available empirical evidence and misinforms policymaking. Evidence of publication bias is mounting in virtually all fields of empirical research. This paper proposes the endogenous kink (EK) meta-regression model as a novel method of publication bias correction. The EK method fits a piecewise linear meta-regression of…

The extensive literature on research co-creation is mostly based on problems being treated as clearly defined and solvable. What is the impact on co-creation when problems are complex, with the following characteristics: difficult to delimit, contested definitions, multiple uncertainties and unresolvable unknowns, constraints on what can be done,…

Parallel to the increasing level of maturity of the field of research on higher education, an increasing number of scholarly works aims at synthesising and presenting overviews of the field. We identify three important pitfalls these previous studies struggle with, i.e. a limited scope, a lack of a content-related analysis, and/or a lack of an…

This study shows that residual variation can cause problems related to scaling in exponential random graph models (ERGM). Residual variation is likely to exist when there are unmeasured variables in a model--even those uncorrelated with other predictors--or when the logistic form of the model is inappropriate. As a consequence, coefficients cannot…

In this article, the authors provide a response to the special issue on "The Science of Teacher Professional Development: Iterative Design Studies Across Content Areas." In doing so, they present the framework of professional development (PD) enactment developed by Mary Kennedy and apply it to the three studies highlighted in this…

Data analysis is a significant methodological component when conducting quantitative education studies. Guidelines for conducting data analyses in quantitative education studies are common but often underemphasize four important methodological components impacting the validity of inferences: quality of constructed measures, proper handling of…

Purpose: Trust is a key component of successful schools. Although scholars widely agree that trust is multifaceted, there is less agreement about the number and nature of these factors. In the October 2016 issue of "Educational Administration Quarterly," C. M. Adams and Miskell (see EJ1112413) argued that their Teacher Trust of District…

Bayesian item response theory (IRT) modeling stages include (a) specifying the IRT likelihood model, (b) specifying the parameter prior distributions, (c) obtaining the posterior distribution, and (d) making appropriate inferences. The latter stage, and the focus of this research, includes model criticism. Choice of priors with the posterior…

This dissertation is aimed at investigating the impact of missing data and evaluating the performance of five selected methods for handling missing responses in the implementation of Cognitive Diagnostic Models (CDMs). The five methods are: a) treating missing data as incorrect (IN), b) person mean imputation (PM), c) two-way imputation (TW), d)…

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…

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…

Background: Stratified medicine seeks to identify patients most likely to respond to treatment. Individual participant data (IPD) network meta-analysis (NMA) models have greater power than individual trials to identify treatment-covariate interactions (TCIs). Treatment-covariate interactions contain "within" and "across" trial…

This paper addresses the wicked problem of measuring the productivity of learning and teaching in higher education. We show how fundamental validity issues and difficulties identified in educational productivity research point to the need for a qualitatively different framework when considering the entire question. We describe the work that needs…