In any meta-analysis, it is critically important to report the dispersion in effects as well as the mean effect. If an intervention has a moderate clinical impact "on average" we also need to know if the impact is moderate for all relevant populations, or if it varies from trivial in some to major in others. Or indeed, if the…

Sensitivity analysis, a statistical method crucial for validating inferences across disciplines, quantifies the conditions that could alter conclusions (Razavi et al., 2021). One line of work is rooted in linear models and foregrounds the sensitivity of inferences to the strength of omitted variables (Cinelli & Hazlett, 2019; Frank, 2000). A…

The purpose of this manuscript is to illustrate the value and potential of critical approaches to quantitative research. We begin by providing our positionalities as scholars to situate ourselves within this content. Next, we overview quantitative criticalism and explore tensions inherent within this approach. Following, we discuss four…

Multilevel factor mixture modeling (FMM) is a hybrid of multilevel confirmatory factor analysis (CFA) and multilevel latent class analysis (LCA). It allows researchers to examine population heterogeneity at the within level, between level, or both levels. This tutorial focuses on explicating the model specification of multilevel FMM that considers…

As a measure of heterogeneity in meta-analysis, the coefficient of variation (CV) has been recently considered, providing researchers with a complement to the very popular I[superscript 2] measure. While I[superscript 2] measures the proportion of total variance that is due to variance of the random effects, the CV is the ratio of the standard…

The nonequivalent groups with anchor test (NEAT) design is widely used in test equating. Under this design, two groups of examinees are administered different test forms with each test form containing a subset of common items. Because test takers from different groups are assigned only one test form, missing score data emerge by design rendering…

Qualitative thematic analysis is a commonly used and widely applicable form of qualitative analysis, though it can be challenging to implement. Due to its use across research questions, qualitative traditions, and fields, thematic analysis is also prevalent in mixed methods studies. Despite its widespread use, the term "thematic…

Extracting data from studies is the norm in meta-analyses, enabling researchers to generate effect sizes when raw data are otherwise not available. While there has been a general push for increased reproducibility in meta-analysis, the transparency and reproducibility of the data extraction phase is still lagging behind. Unfortunately, there is…

In this article we find the thermodynamics of some large N particles systems and some small N particles classical systems using micro canonical ensemble. Small N particle systems are seldom done in textbooks, since statistical mechanics(SM) systems work for large N systems. We show that small N systems will help the students to get an insight…

Common sense is a dynamic concept and it is natural that our (statistical) common sense lags behind the development of statistical science. What is not so easy to understand is why common sense lags behind as much as it does. We conduct a survey among Japanese students and provide examples and tentative explanations of a number of statistical…

Hamdani et al. recently provided guidance for prospective authors on a wide range of issues encountered in quantitative research papers submitted for review at the "Journal of Management Education." Building on their insights, this essay focuses on experimental designs and provides more specific guidance and recommendations for…

This article is concerned with a subset of numerically stable and scalable algorithms useful to support computationally complex psychometric models in the era of machine learning and massive data. The subset selected here is a core set of numerical methods that should be familiar to computational psychometricians and considers whitening transforms…

There are two schools of thought in statistical analysis, frequentist, and Bayesian. Though the two approaches produce similar estimations and predictions in large-sample studies, their interpretations are different. Bland Altman analysis is a statistical method that is widely used for comparing two methods of measurement. It was originally…

Partially specified correlation matrices (not to be confused with matrices with missing data or EM-correlation matrices) can appear in research settings such as integrative data analyses, quantitative systematic reviews or whenever the study design only allows for the collection of certain variables. Although approaches to fill in these missing…

The population relationship between coefficient alpha and scale reliability is studied in the widely used setting of unidimensional multicomponent measuring instruments. It is demonstrated that for any set of component loadings on the common factor, regardless of the extent of their inequality, the discrepancy between alpha and reliability can be…