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…

Most current statistics courses include some instruction relevant to causal inference. Whether this instruction is incorporated as material on randomized experiments or as an interpretation of associations measured by correlation or regression coefficients, the way in which this material is presented may have important implications for…

One part of COVID-19's staggering impact on education has been to suspend or fundamentally alter ongoing education research projects. This article addresses how to analyze the simple but fundamental example of a multi-cohort study in which student assessment data for the final cohort are missing because schools were closed, learning was virtual,…

It is now widely accepted that the standard inferential toolkit used by the scientific research community--null-hypothesis significance testing (NHST)--is not fit for purpose. Yet despite the threat posed to the scientific enterprise, there is no agreement concerning alternative approaches for evidence assessment. This lack of consensus reflects…

The use of big data in higher education has evolved rapidly with a focus on the practical application of new tools and methods for supporting learning. In this paper, we depart from the core emphasis on application and delve into a mostly neglected aspect of the big data conversation in higher education. Drawing on developments in cognate…

Although social scientists devote considerable effort to mitigating measurement error during data collection, they often ignore the issue during data analysis. And although many statistical methods have been proposed for reducing measurement error-induced biases, few have been widely used because of implausible assumptions, high levels of model…

Engaging students in active learning can enhance their understanding and appreciation of a subject such as statistics. Classroom activities and projects help to engage students and further promote the learning process. In this paper, an activity investigating the influence of population size and wealth on the medal counts from the 2012 London…

The use of confidence intervals (CIs) as an addition or as an alternative to null hypothesis significance testing (NHST) has been promoted as a means to make researchers more aware of the uncertainty that is inherent in statistical inference. Little is known, however, about whether presenting results via CIs affects how readers judge the…

In this paper the use of the Rasch model is explored as a transparent, systematic and theoretically underpinned response to quality issues that are widely recognised as problematic in the refinement of Likert scale questionnaires. Key issues are the choice of length of scale, the pursuit of a favourable estimate of Cronbach's alpha at the possible…

The purpose of the research paper was to investigate the effect of eclectic learning approach on the academic achievement and retention of students in English at elementary level. A sample of forty students of 8th grade randomly selected from Government Boys High School Khurram District Karak was used. It was an experimental study and that's why…

This handbook is intended to help government, university, private sector, and other users become better acquainted with the concepts and data underlying the Department of Agriculture's statistical series. The introduction reviews what various pieces of federal legislation say about the computation of agricultural production costs by the U.S.…

A method for drawing inferences from complex samples is based on Rubin's approach to missing data in survey research. Standard procedures for drawing such inferences do not apply when the variables of interest are not observed directly, but must be inferred from secondary random variables which depend on the variables of interest stochastically.…