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Showing 1 to 15 of 27 results Save | Export
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John Mart V. DelosReyes; Miguel A. Padilla – Journal of Experimental Education, 2024
Estimating confidence intervals (CIs) for the correlation has been a challenge because the correlation sampling distribution changes depending on the correlation magnitude. The Fisher z-transformation was one of the first attempts at estimating correlation CIs but has historically shown to not have acceptable coverage probability if data were…
Descriptors: Research Problems, Correlation, Intervals, Computation
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Raykov, Tenko; Doebler, Philipp; Marcoulides, George A. – Measurement: Interdisciplinary Research and Perspectives, 2022
This article is concerned with the large-sample parameter estimator behavior in applications of Bayesian confirmatory factor analysis in behavioral measurement. The property of strong convergence of the popular Bayesian posterior median estimator is discussed, which states numerical convergence with probability 1 of the resulting estimates to the…
Descriptors: Bayesian Statistics, Measurement Techniques, Correlation, Factor Analysis
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Metsämuuronen, Jari – Practical Assessment, Research & Evaluation, 2022
The reliability of a test score is usually underestimated and the deflation may be profound, 0.40 - 0.60 units of reliability or 46 - 71%. Eight root sources of the deflation are discussed and quantified by a simulation with 1,440 real-world datasets: (1) errors in the measurement modelling, (2) inefficiency in the estimator of reliability within…
Descriptors: Test Reliability, Scores, Test Items, Correlation
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Kárász, Judit T.; Széll, Krisztián; Takács, Szabolcs – Quality Assurance in Education: An International Perspective, 2023
Purpose: Based on the general formula, which depends on the length and difficulty of the test, the number of respondents and the number of ability levels, this study aims to provide a closed formula for the adaptive tests with medium difficulty (probability of solution is p = 1/2) to determine the accuracy of the parameters for each item and in…
Descriptors: Test Length, Probability, Comparative Analysis, Difficulty Level
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Hung, Su-Pin; Huang, Hung-Yu – Journal of Educational and Behavioral Statistics, 2022
To address response style or bias in rating scales, forced-choice items are often used to request that respondents rank their attitudes or preferences among a limited set of options. The rating scales used by raters to render judgments on ratees' performance also contribute to rater bias or errors; consequently, forced-choice items have recently…
Descriptors: Evaluation Methods, Rating Scales, Item Analysis, Preferences
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Phillips, Gary W.; Jiang, Tao – Practical Assessment, Research & Evaluation, 2016
Power analysis is a fundamental prerequisite for conducting scientific research. Without power analysis the researcher has no way of knowing whether the sample size is large enough to detect the effect he or she is looking for. This paper demonstrates how psychometric factors such as measurement error and equating error affect the power of…
Descriptors: Error of Measurement, Statistical Analysis, Equated Scores, Sample Size
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Inzunsa Cazares, Santiago – North American Chapter of the International Group for the Psychology of Mathematics Education, 2016
This article presents the results of a qualitative research with a group of 15 university students of social sciences on informal inferential reasoning developed in a computer environment on concepts involved in the confidence intervals. The results indicate that students developed a correct reasoning about sampling variability and visualized…
Descriptors: Qualitative Research, College Students, Inferences, Logical Thinking
Apaloo, Francis – Online Submission, 2013
A key issue in quasi-experimental studies and also with many evaluations which required a treatment effects (i.e. a control or experimental group) design is selection bias (Shadish el at 2002). Selection bias refers to the selection of individuals, groups or data for analysis such that proper randomization is not achieved, thereby ensuring that…
Descriptors: Quasiexperimental Design, Probability, Scores, Least Squares Statistics
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Algina, James; Keselman, H. J.; Penfield, Randall D. – Educational and Psychological Measurement, 2010
The increase in the squared multiple correlation coefficient ([delta]R[superscript 2]) associated with a variable in a regression equation is a commonly used measure of importance in regression analysis. Algina, Keselman, and Penfield found that intervals based on asymptotic principles were typically very inaccurate, even though the sample size…
Descriptors: Computation, Statistical Analysis, Correlation, Statistical Inference
Jia, Yue; Stokes, Lynne; Harris, Ian; Wang, Yan – Educational Testing Service, 2011
Estimation of parameters of random effects models from samples collected via complex multistage designs is considered. One way to reduce estimation bias due to unequal probabilities of selection is to incorporate sampling weights. Many researchers have been proposed various weighting methods (Korn, & Graubard, 2003; Pfeffermann, Skinner,…
Descriptors: Computation, Statistical Bias, Sampling, Statistical Analysis
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Dunst, Carl J.; Hamby, Deborah W. – Journal of Intellectual & Developmental Disability, 2012
This paper includes a nontechnical description of methods for calculating effect sizes in intellectual and developmental disability studies. Different hypothetical studies are used to illustrate how null hypothesis significance testing (NHST) and effect size findings can result in quite different outcomes and therefore conflicting results. Whereas…
Descriptors: Intervals, Developmental Disabilities, Statistical Significance, Effect Size
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Kozak, Marcin – Teaching Statistics: An International Journal for Teachers, 2009
This article suggests how to explain a problem of small sample size when considering correlation between two Normal variables. Two techniques are shown: one based on graphs and the other on simulation. (Contains 3 figures and 1 table.)
Descriptors: Sample Size, Correlation, Predictor Variables, Simulation
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Long, Michael A.; Berry, Kenneth J.; Mielke, Paul W., Jr. – Educational and Psychological Measurement, 2009
An exact permutation test is provided for the tetrachoric correlation coefficient. Comparisons with the conventional test employing Student's t distribution demonstrate the necessity of using the permutation approach for small sample sizes and/or disproportionate marginal frequency totals. (Contains 4 tables.)
Descriptors: Statistical Analysis, Correlation, Sample Size, Comparative Analysis
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Jia, Yue; Stokes, Lynne; Harris, Ian; Wang, Yan – Journal of Educational and Behavioral Statistics, 2011
In this article, we consider estimation of parameters of random effects models from samples collected via complex multistage designs. Incorporation of sampling weights is one way to reduce estimation bias due to unequal probabilities of selection. Several weighting methods have been proposed in the literature for estimating the parameters of…
Descriptors: Sampling, Computation, Statistical Bias, Statistical Analysis
Kustos, Paul Nicholas – ProQuest LLC, 2010
Student difficulty in the study of probability arises in intuitively-based misconceptions derived from heuristics. One such heuristic, the one of note for this research study, is that of representativeness, in which an individual informally assesses the probability of an event based on the degree to which the event is similar to the sample from…
Descriptors: Sample Size, Self Efficacy, Heuristics, Likert Scales
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