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Widaman, Keith F. – Educational and Psychological Measurement, 2023
The import or force of the result of a statistical test has long been portrayed as consistent with deductive reasoning. The simplest form of deductive argument has a first premise with conditional form, such as p[right arrow]q, which means that "if p is true, then q must be true." Given the first premise, one can either affirm or deny…
Descriptors: Hypothesis Testing, Statistical Analysis, Logical Thinking, Probability
Yi, Zhihui; Schreiber, James B.; Paliliunas, Dana; Barron, Becky F.; Dixon, Mark R. – Journal of Behavioral Education, 2021
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…
Descriptors: Research Problems, Data Analysis, Statistical Analysis, Probability
Kulinskaya, Elena; Hoaglin, David C. – Research Synthesis Methods, 2023
For estimation of heterogeneity variance T[superscript 2] in meta-analysis of log-odds-ratio, we derive new mean- and median-unbiased point estimators and new interval estimators based on a generalized Q statistic, Q[subscript F], in which the weights depend on only the studies' effective sample sizes. We compare them with familiar estimators…
Descriptors: Q Methodology, Statistical Analysis, Meta Analysis, Intervals
Raykov, Tenko; Marcoulides, George A.; Pusic, Martin – Measurement: Interdisciplinary Research and Perspectives, 2021
An interval estimation procedure is discussed that can be used to evaluate the probability of a particular response for a binary or binary scored item at a pre-specified point along an underlying latent continuum. The item is assumed to: (a) be part of a unidimensional multi-component measuring instrument that may contain also polytomous items,…
Descriptors: Item Response Theory, Computation, Probability, Test Items
Kim, Eunsook; von der Embse, Nathaniel – Educational and Psychological Measurement, 2021
Although collecting data from multiple informants is highly recommended, methods to model the congruence and incongruence between informants are limited. Bauer and colleagues suggested the trifactor model that decomposes the variances into common factor, informant perspective factors, and item-specific factors. This study extends their work to the…
Descriptors: Probability, Models, Statistical Analysis, Congruence (Psychology)
Trafimow, David – International Journal of Social Research Methodology, 2019
Although the null hypothesis significance testing procedure is problematic, many still favor the use of "p"-values as indicating the state of evidence against the model used to generate the "p"-value. From this perspective, "p"-values benefit science; or would benefit science if used correctly. In contrast, the novel…
Descriptors: Hypothesis Testing, Models, Taxonomy, Probability
Iannario, Maria; Manisera, Marica; Piccolo, Domenico; Zuccolotto, Paola – Sociological Methods & Research, 2020
In analyzing data from attitude surveys, it is common to consider the "don't know" responses as missing values. In this article, we present a statistical model commonly used for the analysis of responses/evaluations expressed on Likert scales and extended to take into account the presence of don't know responses. The main objective is to…
Descriptors: Response Style (Tests), Likert Scales, Statistical Analysis, Models
Wallin, Gabriel; Wiberg, Marie – Journal of Educational and Behavioral Statistics, 2019
When equating two test forms, the equated scores will be biased if the test groups differ in ability. To adjust for the ability imbalance between nonequivalent groups, a set of common items is often used. When no common items are available, it has been suggested to use covariates correlated with the test scores instead. In this article, we reduce…
Descriptors: Equated Scores, Test Items, Probability, College Entrance Examinations
Leite, Walter L.; Aydin, Burak; Gurel, Sungur – Journal of Experimental Education, 2019
This Monte Carlo simulation study compares methods to estimate the effects of programs with multiple versions when assignment of individuals to program version is not random. These methods use generalized propensity scores, which are predicted probabilities of receiving a particular level of the treatment conditional on covariates, to remove…
Descriptors: Probability, Weighted Scores, Monte Carlo Methods, Statistical Bias
Groth, Randall E. – Journal of Statistics Education, 2019
The Common Core State Standards for Mathematics have a widespread impact on children's statistical learning opportunities. The Grade 6 standards are particularly ambitious in the goals they set. In this critique, experiences helping children work toward the Grade 6 Common Core statistics expectations are used in conjunction with previous research…
Descriptors: Common Core State Standards, Grade 4, Grade 5, Grade 6
Zane, Len – Honors in Practice, 2020
Many of the numbers used to assess students are statistical in nature. The theoretical context underlying the production of a typical number or statistic used in student assessment is presented. The author urges readers to recognize objective data as subjective information and to carefully consider the numbers that often determine admission,…
Descriptors: Student Evaluation, Statistical Analysis, Honors Curriculum, Admission Criteria
Doroudi, Shayan; Brunskill, Emma – Grantee Submission, 2017
In this paper, we investigate two purported problems with Bayesian Knowledge Tracing (BKT), a popular statistical model of student learning: "identifiability" and "semantic model degeneracy." In 2007, Beck and Chang stated that BKT is susceptible to an "identifiability problem"--various models with different…
Descriptors: Bayesian Statistics, Research Problems, Statistical Analysis, Models
Tampieri, Alessandro – Education Economics, 2016
This paper argues that assortative matching may explain over-education. Education determines individuals' income and, due to the presence of assortative matching, the quality of partners in personal, social and working life. Thus, an individual acquires education to improve the expected partners' quality. However, since every individual of the…
Descriptors: Educational Attainment, Overachievement, Education Work Relationship, Interpersonal Relationship
Henman, Paul; Brown, Scott D.; Dennis, Simon – Australian Universities' Review, 2017
In 2015, the Australian Government's Excellence in Research for Australia (ERA) assessment of research quality declined to rate 1.5 per cent of submissions from universities. The public debate focused on practices of gaming or "coding errors" within university submissions as the reason for this outcome. The issue was about the…
Descriptors: Rating Scales, Foreign Countries, Universities, Achievement Rating
Keller, Bryan; Tipton, Elizabeth – Journal of Educational and Behavioral Statistics, 2016
In this article, we review four software packages for implementing propensity score analysis in R: "Matching, MatchIt, PSAgraphics," and "twang." After briefly discussing essential elements for propensity score analysis, we apply each package to a data set from the Early Childhood Longitudinal Study in order to estimate the…
Descriptors: Computer Software, Probability, Statistical Analysis, Longitudinal Studies