The recent commentary by Beaujean and Farmer (2020) on the original paper by Dixon et al. (2019) serves a cautionary tale of selective p-values, the law of small N sizes, and the type-II error. We believe these authors have crafted a somewhat questionable argument in which only 57% of the original Dixon et al. data were re-analyzed, based on a…

Meta-analysis and structural equation modeling (SEM) are 2 of the most prominent statistical techniques employed in the behavioral, medical, and social sciences. They each have their own well-established research communities, terminologies, statistical models, software packages, and journals ("Research Synthesis Methods" and…

The importance of data analysis software in graduate programs in education and post-graduate educational research is self-evident. However the role of this software in facilitating supererogated statistical practice versus "cookbookery" is unclear. The need to rigorously document the role of data analysis software in students' graduate…

The authors of the focus article describe an important issue related to the use and interpretation of causal indicators within the context of structural equation modeling (SEM). In the focus article, the authors illustrate with simulated data the effects of omitting a causal indicator. Since SEMs are used extensively in the social and behavioral…

Building on the work of Bollen (2007) and Bollen & Bauldry (2011), Bainter and Bollen (this issue) clarifies several points of confusion in the literature regarding causal indicator models. This author would certainly agree that the effect indicator (reflective) measurement model is inappropriate for some indicators (such as the social…

The van der Linden article (this issue) provides a roadmap for future research in equating. My belief is that the roadmap begins and ends with collecting auxiliary data that can be utilized to provide improved equating, especially when data are sparse or equating beyond simple moments is desired.

In this commentary, we offer a set of visual tools that can assist education researchers, especially those in the field of mathematics, in developing cohesiveness from a mixed methods perspective, commencing at a study's research questions and literature review, through its data collection and analysis, and finally to its results. This expounds…

In answering the question "What is the next trend in usage statistics in libraries?" an eclectic group of respondents has presented an assortment of possibilities, suggestions, complaints and, of course, questions of their own. Undoubtedly, usage statistics collection, interpretation, and application are areas of growth and increasing complexity…

Peter Wylie is a man of many contradictions: a statistician and a storyteller, an introvert who loves an audience, and a self-described data geek with a passion for his work and the people it helps. Wylie is one of the pioneers of predictive modeling, the statistical analysis that uses data to drive educational institutions and nonprofits toward…

Data collection and analysis are frequently neglected by school leaders over the course of the decision-making process. All schools gather large amounts of information about students and teachers, but most data are used to satisfy administrative requirements rather than evaluate school improvement in a systematic fashion. Apprehension regarding…

Over the second half of the twentieth century, changes occurred in parent reports of their engagement in cognitive activities with their young children in the United States. This article argues that the growing trend of "parenting for cognitive development" in young children in the latter half of the twentieth century is associated with the…

We argue that the report by Templer and Arikawa contains misleading conclusions and is based upon faulty collection and analysis of data. The report fails to hold up for quality of data, statistical analysis, and the logic of science.

Calls for simplicity when presenting data on student achievement. Data should help teachers improve teaching and learning, and focus on specific goals such as determining how many students are succeeding in a subject and, within that subject, what are the areas of strength or weakness. (Contains 22 references.) (WFA)

The most advantageous relationship between computer technology and institutional research is considered. Three potential problem areas are discussed: those associated with a central data processing center, those germane to minicomputers or terminals within the institutional research office, and those nondiscriminating types which cover both…

Principles of scientific data accumulation and evidence-based practices are vehicles of professional enhancement. In this article, the author argues that a scientific knowledge base exists descriptive of the relationship between teachers' activities and student learning. This database appears barely recognised however, for reasons including (a)…