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…

In this article, the author will discuss processes used by quantitative researchers to render judgments and decisions about the results of their statistical analyses, highlighting what "'p'-values" represent and how "p"-values became ubiquitous in quantitative social science research. Suggestions for alternative ways to measure…

Human creativity finds in artistic practices one of its most admirable forms. Most of the studies about artistic practices have used qualitative approaches, focusing on the conceptual structures conveyed by the artwork. Few studies have used quantitative approaches with the potential to be generalized. This study has focused on developing a…

Effective undergraduate statistical education requires training using real-world data. Textbook datasets seldom match the complexities and messiness of real-world data and finding these datasets can be challenging for educators. Consulting and industrial datasets often have nondisclosure agreements. Academic datasets often require subject area…

Q methodology is a unique, yet underutilized methodology designed specifically to scientifically study subjectivity. Q, as it is most often referred to, is an appropriate methodology whenever a researcher is interested in uncovering and describing the multiple divergent viewpoints on any topic. Such discovery of viewpoints provides insight into…

In today's data-driven and data-informed educational landscape, leaders face increasing pressure to make decisions and present results based on what appear to be comprehensive statistical analyses. However, the ethical implications of these responsibilities can be complex, particularly when statistical results carry the potential to be…

Classification and Regression Tree (CART) analysis is a statistical modeling approach that uses quantitative data to predict future outcomes by generating decision trees. CART analysis can be useful for educators to inform their decision-making. For example, educators can use a decision tree from a CART analysis to identify students who are most…

This quantitative study investigated the relationship between teacher self-efficacy, maximizing decision-making tendencies, and utilization of educational technology resources. The study utilized the Teacher Sense of Self-Efficacy Scale (TSES), the Maximizing Tendency Scale (MTS-7), and teacher use of educational technology surveys to determine if…

In educational studies, the paradigm war over quantitative and qualitative research approaches has raged for more than half a century. The focus in the late twentieth century was on the distinction between the two approaches, and the motivation was to retain one of the approaches' supremacy. Since the early twenty-first century, there has been a…

At last, a comprehensive guide that meets psychologists and other social scientists' growing need to master the tools of statistical prediction. "Prediction Statistics for Psychological Assessment," by R. Karl Hanson, is the first book to teach students and practitioners the nuts and bolts of prediction statistics, while illustrating the…

Estimating and accounting for statistical uncertainty have become essential in today's information age, and crucial for cultivating a sound decision making citizenry. Engaging with statistical uncertainty early on can support the gradual development of uncertainty-related considerations that are often challenging to foster at any age. Statistical…

The growing fiscal cost of K-12 teacher pension plans and pension-induced labor market distortions have led to calls for teacher pension reforms. Dynamic structural econometric models are a useful way to analyze the fiscal and staffing consequences of current and alternative retirement plans. This article lays out the benefits of the structural…

This paper aims to unsettle assumptions of generalizability and representativeness in quantitative research using queer framings and positionalities. We argue that generalizability and representativeness are tools of supremacist dominance that reinforce harmful and essentialist categories of identities for the false purpose of statistical…

A new index of item discrimination power (IDP), dimension-corrected Somers' D (D2) is proposed. Somers' D is one of the superior alternatives for item-total- (Rit) and item-rest correlation (Rir) in reflecting the real IDP with items with scales 0/1 and 0/1/2, that is, up to three categories. D also reaches the extreme value +1 and -1 correctly…

How researchers use statistical analyses shapes their research toward or away from an anti-racist agenda. In this article, we demonstrate how developmental scientists can use the QuantCrit framework to critically examine the process of conducting quantitative analyses. In particular, we focus on mixture modeling to clearly demonstrate how the…