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Gonzalez, Oscar – Educational and Psychological Measurement, 2023
When scores are used to make decisions about respondents, it is of interest to estimate classification accuracy (CA), the probability of making a correct decision, and classification consistency (CC), the probability of making the same decision across two parallel administrations of the measure. Model-based estimates of CA and CC computed from the…
Descriptors: Classification, Accuracy, Intervals, Probability
Weber, Frank; Knapp, Guido; Glass, Änne; Kundt, Günther; Ickstadt, Katja – Research Synthesis Methods, 2021
There exists a variety of interval estimators for the overall treatment effect in a random-effects meta-analysis. A recent literature review summarizing existing methods suggested that in most situations, the Hartung-Knapp/Sidik-Jonkman (HKSJ) method was preferable. However, a quantitative comparison of those methods in a common simulation study…
Descriptors: Meta Analysis, Computation, Intervals, Statistical Analysis
Du, Han; Enders, Craig; Keller, Brian; Bradbury, Thomas N.; Karney, Benjamin R. – Grantee Submission, 2022
Missing data are exceedingly common across a variety of disciplines, such as educational, social, and behavioral science areas. Missing not at random (MNAR) mechanism where missingness is related to unobserved data is widespread in real data and has detrimental consequence. However, the existing MNAR-based methods have potential problems such as…
Descriptors: Bayesian Statistics, Data Analysis, Computer Simulation, Sample Size
Liang, Xinya – Educational and Psychological Measurement, 2020
Bayesian structural equation modeling (BSEM) is a flexible tool for the exploration and estimation of sparse factor loading structures; that is, most cross-loading entries are zero and only a few important cross-loadings are nonzero. The current investigation was focused on the BSEM with small-variance normal distribution priors (BSEM-N) for both…
Descriptors: Factor Structure, Bayesian Statistics, Structural Equation Models, Goodness of Fit
Trafimow, David – Educational and Psychological Measurement, 2017
There has been much controversy over the null hypothesis significance testing procedure, with much of the criticism centered on the problem of inverse inference. Specifically, p gives the probability of the finding (or one more extreme) given the null hypothesis, whereas the null hypothesis significance testing procedure involves drawing a…
Descriptors: Statistical Inference, Hypothesis Testing, Probability, Intervals
Liu, Yang; Yang, Ji Seung – Journal of Educational and Behavioral Statistics, 2018
The uncertainty arising from item parameter estimation is often not negligible and must be accounted for when calculating latent variable (LV) scores in item response theory (IRT). It is particularly so when the calibration sample size is limited and/or the calibration IRT model is complex. In the current work, we treat two-stage IRT scoring as a…
Descriptors: Intervals, Scores, Item Response Theory, Bayesian Statistics
Stamey, James D.; Beavers, Daniel P.; Sherr, Michael E. – Sociological Methods & Research, 2017
Survey data are often subject to various types of errors such as misclassification. In this article, we consider a model where interest is simultaneously in two correlated response variables and one is potentially subject to misclassification. A motivating example of a recent study of the impact of a sexual education course for adolescents is…
Descriptors: Bayesian Statistics, Classification, Models, Correlation
Abayomi, Kobi; Pizarro, Gonzalo – Social Indicators Research, 2013
We offer a straightforward framework for measurement of progress, across many dimensions, using cross-national social indices, which we classify as linear combinations of multivariate country level data onto a univariate score. We suggest a Bayesian approach which yields probabilistic (confidence type) intervals for the point estimates of country…
Descriptors: Bayesian Statistics, Intervals, Guidelines, Measurement
Kaplan, David; Chen, Jianshen – Psychometrika, 2012
A two-step Bayesian propensity score approach is introduced that incorporates prior information in the propensity score equation and outcome equation without the problems associated with simultaneous Bayesian propensity score approaches. The corresponding variance estimators are also provided. The two-step Bayesian propensity score is provided for…
Descriptors: Intervals, Bayesian Statistics, Scores, Prior Learning
Gelman, Andrew; Hill, Jennifer; Yajima, Masanao – Journal of Research on Educational Effectiveness, 2012
Applied researchers often find themselves making statistical inferences in settings that would seem to require multiple comparisons adjustments. We challenge the Type I error paradigm that underlies these corrections. Moreover we posit that the problem of multiple comparisons can disappear entirely when viewed from a hierarchical Bayesian…
Descriptors: Intervals, Comparative Analysis, Inferences, Error Patterns
Patching, Geoffrey R.; Englund, Mats P.; Hellstrom, Ake – Journal of Experimental Psychology: Human Perception and Performance, 2012
Despite the importance of both response probability and response time for testing models of choice, there is a dearth of chronometric studies examining systematic asymmetries that occur over time- and space-orders in the method of paired comparisons. In this study, systematic asymmetries in discriminating the magnitude of paired visual stimuli are…
Descriptors: Computation, Visual Stimuli, Probability, Reaction Time
Makel, Matthew C.; Lee, Seon-Young; Olszewki-Kubilius, Paula; Putallaz, Martha – Journal of Educational Psychology, 2012
Big-fish-little-pond effect (BFLPE) research (e.g., Marsh & Parker, 1984) has found that perceptions of academic ability are generally positively related to individual ability and negatively related to classroom and school average ability. However, BFLPE research typically relies on environmental differences as a between-subjects factor. Unlike…
Descriptors: Academic Ability, Academic Aspiration, Educational Environment, Self Concept
Biesanz, Jeremy C.; Falk, Carl F.; Savalei, Victoria – Multivariate Behavioral Research, 2010
Theoretical models specifying indirect or mediated effects are common in the social sciences. An indirect effect exists when an independent variable's influence on the dependent variable is mediated through an intervening variable. Classic approaches to assessing such mediational hypotheses (Baron & Kenny, 1986; Sobel, 1982) have in recent years…
Descriptors: Computation, Intervals, Models, Monte Carlo Methods
Choi, Kilchan; Seltzer, Michael – Journal of Educational and Behavioral Statistics, 2010
In studies of change in education and numerous other fields, interest often centers on how differences in the status of individuals at the start of a period of substantive interest relate to differences in subsequent change. In this article, the authors present a fully Bayesian approach to estimating three-level Hierarchical Models in which latent…
Descriptors: Simulation, Computation, Models, Bayesian Statistics
Hutchins, Sean; Palmer, Caroline – Journal of Experimental Psychology: Human Perception and Performance, 2008
The authors explore priming effects of pitch repetition in music in 3 experiments. Musically untrained participants heard a short melody and sang the last pitch of the melody as quickly as possible. Each experiment manipulated (a) whether or not the tone to be sung (target) was heard earlier in the melody (primed) and (b) the prime-target distance…
Descriptors: Music, Drills (Practice), Phonology, Intonation
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