Children's fuzziness leads to increased variance in the data, data loss, and high dropout rates in developmental studies. This study investigated the importance of 20 factors on the person (child, caregiver, experimenter) and situation (task, method, time, and date) level for the data quality as indicated via the number of valid trials in 11…

Background/Context: Confirmatory factor analysis (CFA) model is a commonly adopted framework to estimate and test a measurement model. Once a well-fitting final CFA model is selected, the selected model may be used to test structural relationships of the latent constructs with other variables, to construct a test with desired reliability and…

Simple matrix sampling planned missing (SMS PD) design, introduce missing data patterns that lead to covariances between variables that are not jointly observed, and create difficulties for analyses other than mean and variance estimations. Based on prior research, we adopted a new multigroup confirmatory factor analysis (CFA) approach to handle…

Scholars study representative international surveys to understand cross-cultural differences in mentality patterns, which are measured via complex multi-item constructs. Methodologists in this field insist with increasing vigor that detecting "non-invariance" in how a construct's items associate with each other in different national…

Although parallel analysis has been found to be an accurate method for determining the number of factors in many conditions with complete data, its application under missing data is limited. The existing literature recommends that, after using an appropriate multiple imputation method, researchers either apply parallel analysis to every imputed…

Determining the number of factors in exploratory factor analysis is arguably the most crucial decision a researcher faces when conducting the analysis. While several simulation studies exist that compare various so-called factor retention criteria under different data conditions, little is known about the impact of missing data on this process.…

This paper evaluates the use of Factor Analysis (FA) in English education research in Korea and suggests improvements in methodology. A detailed coding protocol was used to review 179 FA cases from 12 major English education journals (2014-2023). The review identified several key issues, including small sample sizes and lenient criteria for sample…

This article addresses conceptual and methodological shortcomings regarding conducting and interpreting intelligence test factor analytic research that appeared in the Decker, S. L., Bridges, R. M., Luedke, J. C., & Eason, M. J. (2020). Dimensional evaluation of cognitive measures: Methodological confounds and theoretical concerns.…

The use of structural equation modeling (SEM) techniques in social work has increased over the last two decades. We therefore conducted a systematic review to understand the extent to which SEM is utilized in social work research, given that statistical training is now becoming a part of social work doctoral education. For our review, we utilized…

Factorial surveys use a population of vignettes to elicit respondents' attitudes or beliefs about different hypothetical scenarios. However, the vignette population is frequently too large to be assessed by each respondent. Experimental designs such as randomized block confounded factorial (RBCF) designs, D-optimal designs, or random sampling…

This study investigates the performance of robust maximum likelihood (ML) estimators when fitting and evaluating small sample latent growth models with non-normal missing data. Results showed that the robust ML methods could be used to account for non-normality even when the sample size is very small (e.g., N < 100). Among the robust ML…

This case study describes a Q methodology study which captured and analyzed the viewpoints of 45 UK teachers online. The teachers might liken their participation in the study to a "card sort" activity: their relative placement of statement cards revealed their opinions of mastery in mathematics. Factor analysis of the completed sorts…

The purposes of this manuscript are to identify common statistical mistakes in sport management, and to provide scholars with suggestions on how to develop and improve the quality of quantitative research. We have reviewed articles published from 2001 to 2017 in the "Journal of Sport Management," "Sport Management Review,"…

Sport management research has evolved significantly despite its relatively short history as an academic discipline. Although the pace of scholarly progress has been impressive, the extent to which many research efforts have aided sport management in becoming a distinct academic discipline is, at times, questionable. A major challenge many scholars…

In the field of social sciences, certain tasks, such as the identification of typologies and the characterization of groups of individuals according to a set of questions, tend to pose a challenge for researchers. Further complications arise if the chosen rating scale is from 0 to 10, since the responses can be treated either as metric or…