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…

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…

Quantitative literacy, the ability to discriminate between good and bad data, the disposition to use quantitative information to think through complex problems are capacities that educators across fields should be helping students develop. Burke leads the reader to this conclusion through an extended example of income distribution, clarified and…

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.

Discussion of the need for systematic methods for summarizing single-participant research describes various approaches for quantitative synthesis and reviews conclusions of completed synthesis efforts. The issue of whether outcomes of single-participant research can be represented by a single common metric is addressed with the recommendation that…

The mathematical extension from scalars to matrices as a prerequisite for univariate to multivariate generalizations of statistical concepts and methods is discussed. One reason for several alternative techniques is the multitude of ways to generalize from univariate concepts to multivariate concepts. The additional complexity, and lack of…

Discusses current practices for statistical assessments of employment discrimination and suggests nonstatistical techniques that can be used to aid in interpreting results of statistical analyses. The techniques incorporate principles of Boolean algebra and allow holistic comparison of categories of similarly situated individuals. (CMG)

Discusses the purposes and benefits of data synthesis, explaining the major techniques of extracting information from related studies and using it to explain conflicting outcomes. Stresses the importance of the analyst's attention to detailed features of each study and describes the steps of a systematic approach to synthesis. (SK)

The author contends that model misspecification can occur even after researchers have selected the generally most appropriate class of methods, or general linear model techniques. It is suggested specifically that canonical correlation analysis may provide more meaningful results, as compared with regression, particularly if analysis is augmented…

Important differences in the theory and practice of quantitative and qualitative research methodologies are highlighted. This article suggests that each of these methodologies can be improved by utilizing key ingredients of the other. (Author/IAH)

Examines difficulties associated with the use of conversational features in the analysis of mother-infant vocalization episodes. Observations of six mother-infant dyads revealed difficulties involving (1) pooling of data; (2) the unit of analysis; and (3) selection of appropriate "expected" values for dyadic parameters used in tests of…

Discusses procedures and considerations involved with secondary analyses of longitudinal databases. Procedures involve (1) formulating questions; (2) creating a feasibility matrix; (3) reformulating questions; (4) creating derived variables; (5) performing data reduction; (6) analyzing data; and (7) interpreting results. Problems associated with…

Data and information needs of college administrators are discussed, along with the uses of information to support decisionmaking. Difficulties in applying information technology to the administration of higher education are briefly reviewed. Data and information are discussed both in definitional and functional terms. Data are defined as either…