The number of meta-analyses of aggregate data has dramatically increased due to the facility of obtaining data from publications and the development of free, easy-to-use, and specialised statistical software. Even when meta-analyses include the same studies, their results may vary owing to different methodological choices. Assessment of the…

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…

Well-chosen covariates boost the design sensitivity of individually and cluster-randomized trials. We provide guidance on covariate selection generating an extensive compilation of single- and multilevel design parameters on student achievement. Embedded in psychometric heuristics, we analyzed (a) covariate "types" of varying…

Previous research extensively studied reasons for and ways to avoid low response rates, but it largely ignored the primary research issue of the degree to which response rates matter, which we address. Methodological survey research on response rates has been concerned with how to increase responsiveness and with the effects of response rates on…

Factor analysis is widely utilized to identify latent factors underlying the observed variables. This paper presents a comprehensive comparative study of two widely used methods for determining the optimal number of factors in factor analysis, the K1 rule, and parallel analysis, along with a more recently developed method, the bass-ackward method.…

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…

The definition of what constitutes a conflict, in terms of both time and events, has been consistently debated in the historical study of social phenomena. What has become increasingly clear, however, is that the methods used to define it are generally biased as they are highly dependent on the perceptions of the researchers who establish them.…

The purpose of this study is to review the status of differential item functioning (DIF) research in language testing, particularly as it relates to the investigation of sources (or causes) of DIF, which is a defining characteristic of the third generation DIF. This review included 110 DIF studies of language tests dated from 1985 to 2019. We…

Educational researchers continue to polarize into 'qualitative' and 'quantitative' camps, with these terms often functioning as global identity markers, rather than as styles of research that are available to anyone. Many scholars have lamented the drawbacks of researchers being siloed into opposing, apparently incommensurable research paradigms,…

Research designs that include planned missing data are gaining popularity in applied education research. These methods have traditionally relied on introducing missingness into data collections using the missing completely at random (MCAR) mechanism. This study assesses whether planned missingness can also be implemented when data are instead…

Common method variance refers to the amount of uncontrolled systematic error leading to biased estimates of scale reliability and validity and to spurious covariance shared among variables due to common method and/or common source employed in survey-based researches. As the extended use of self-report questionnaires is inevitable, numerous studies…

Background: In Malaysia, the mortality from melioidosis infection was reported to be higher than in other infectious diseases. The research on melioidosis is still limited in Malaysia but slightly increasing. Objectives: The objective of the study was to give an overview of the study designs, statistical methods, and comparison of research in…

This study aims to address a gap in the social and behavioral sciences literature concerning interaction effects between latent factors in multiple-group analysis. By comparing two approaches for estimating latent interactions within multiple-group analysis frameworks using simulation studies and empirical data, we assess their relative merits.…

The authors of this article present arguments for why and how qualitative research should be used in economic education. These arguments recognize the nature of economics as a discipline and economics educators' current expertise and preferences. The authors have five goals: (i) clarifying how and why the use of qualitative research in economic…

Meta-analytic models for dependent effect sizes have grown increasingly sophisticated over the last few decades, which has created challenges for a priori power calculations. We introduce power approximations for tests of average effect sizes based upon several common approaches for handling dependent effect sizes. In a Monte Carlo simulation, we…