Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 3 |
| Since 2007 (last 20 years) | 8 |
Descriptor
| Bayesian Statistics | 16 |
| Sampling | 16 |
| Statistical Analysis | 16 |
| Computation | 5 |
| Comparative Analysis | 4 |
| Models | 4 |
| Classification | 3 |
| Correlation | 3 |
| Mathematical Models | 3 |
| Multiple Regression Analysis | 3 |
| Probability | 3 |
| More ▼ | |
Source
Author
| Novick, Melvin R. | 2 |
| Babcock, Ben | 1 |
| Curry, Allen R. | 1 |
| Fyans, Leslie J., Jr. | 1 |
| Geisser, Seymour | 1 |
| Glass, Änne | 1 |
| Guerra-Peña, Kiero | 1 |
| Hedges, Larry V. | 1 |
| Huberty, Carl J. | 1 |
| Ickstadt, Katja | 1 |
| Kaplan, David | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 7 |
| Reports - Research | 7 |
| Reports - Evaluative | 2 |
| Information Analyses | 1 |
| Speeches/Meeting Papers | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
| Elementary and Secondary… | 1 |
Assessments and Surveys
| ACT Assessment | 1 |
| Program for International… | 1 |
What Works Clearinghouse Rating
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
Lee, Hyung Rock; Sung, Jaeyun; Lee, Sunbok – International Journal of Assessment Tools in Education, 2021
Conventional estimators for indirect effects using a difference in coefficients and product of coefficients produce the same results for continuous outcomes. However, for binary outcomes, the difference in coefficient estimator systematically underestimates the indirect effects because of a scaling problem. One solution is to standardize…
Descriptors: Statistical Analysis, Computation, Regression (Statistics), Scaling
Guerra-Peña, Kiero; Steinley, Douglas – Educational and Psychological Measurement, 2016
Growth mixture modeling is generally used for two purposes: (1) to identify mixtures of normal subgroups and (2) to approximate oddly shaped distributions by a mixture of normal components. Often in applied research this methodology is applied to both of these situations indistinctly: using the same fit statistics and likelihood ratio tests. This…
Descriptors: Growth Models, Bayesian Statistics, Sampling, Statistical Inference
Kaplan, David; Su, Dan – Journal of Educational and Behavioral Statistics, 2016
This article presents findings on the consequences of matrix sampling of context questionnaires for the generation of plausible values in large-scale assessments. Three studies are conducted. Study 1 uses data from PISA 2012 to examine several different forms of missing data imputation within the chained equations framework: predictive mean…
Descriptors: Sampling, Questionnaires, Measurement, International Assessment
Pan, Yilin – Society for Research on Educational Effectiveness, 2016
Given the necessity to bridge the gap between what happened and what is likely to happen, this paper aims to explore how to apply Bayesian inference to cost-effectiveness analysis so as to capture the uncertainty of a ratio-type efficiency measure. The first part of the paper summarizes the characteristics of the evaluation data that are commonly…
Descriptors: Resource Allocation, Cost Effectiveness, Bayesian Statistics, Statistical Analysis
McNeish, Daniel – Review of Educational Research, 2017
In education research, small samples are common because of financial limitations, logistical challenges, or exploratory studies. With small samples, statistical principles on which researchers rely do not hold, leading to trust issues with model estimates and possible replication issues when scaling up. Researchers are generally aware of such…
Descriptors: Models, Statistical Analysis, Sampling, Sample Size
Shadish, William R.; Rindskopf, David M.; Hedges, Larry V.; Sullivan, Kristynn J. – Online Submission, 2012
Researchers in the single-case design tradition have debated the size and importance of the observed autocorrelations in those designs. All of the past estimates of the autocorrelation in that literature have taken the observed autocorrelation estimates as the data to be used in the debate. However, estimates of the autocorrelation are subject to…
Descriptors: Bayesian Statistics, Research Design, Correlation, Computation
Babcock, Ben – Applied Psychological Measurement, 2011
Relatively little research has been conducted with the noncompensatory class of multidimensional item response theory (MIRT) models. A Monte Carlo simulation study was conducted exploring the estimation of a two-parameter noncompensatory item response theory (IRT) model. The estimation method used was a Metropolis-Hastings within Gibbs algorithm…
Descriptors: Item Response Theory, Sampling, Computation, Statistical Analysis
Peer reviewedGeisser, Seymour; Kappenman, Russell F. – Psychometrika, 1971
Descriptors: Bayesian Statistics, Mathematics, Probability, Profiles
Meyer, Donald – 1969
One of six summaries of workshop sessions (See TM 000 130), designed to strengthen the evaluation of costly programs and their effects, this handbook presents an analysis of both random and nonrandom sampling errors by application of the Bayesian model. This model attempts to formalize the process and procedures of inference from data through…
Descriptors: Bayesian Statistics, Data Collection, Error Patterns, Models
Larsson, B. – 1972
An experimental study of the efficiency of human information processing is based on the Bayesian model for simple hypothesis testing with fixed binomial sampling. Each of 60 subjects is analyzed with separate ANOVAs focusing on two efficiency variables. Sample size and critical value are also analyzed. Subjects show very different utilization of…
Descriptors: Bayesian Statistics, Cognitive Processes, Hypothesis Testing, Information Processing
Peer reviewedNovick, Melvin R.; And Others – Psychometrika, 1973
This paper develops theory and methods for the application of the Bayesian Model II method to the estimation of binomial proportions and demonstrates its application to educational data. (Author/RK)
Descriptors: Bayesian Statistics, Educational Testing, Mathematical Models, Measurement
PDF pending restorationHuberty, Carl J.; Curry, Allen R. – 1975
A linear classification rule (used with equal covariance matrices) was contrasted with a quadratic rule (used with unequal covariance matrices) for accuracy of internal and external classification. The comparisons were made for seven situations which resulted from combining three data conditions (equal and unequal covariance matrices, minimal and…
Descriptors: Analysis of Covariance, Bayesian Statistics, Classification, Comparative Analysis
Novick, Melvin R.; And Others – 1971
The feasibility and effectiveness of a Bayesian method for estimating regressions in m groups is studied by application of the method to data from the Basic Research Service of The American College Testing Program. Evidence supports the belief that in many testing applications the collateral information obtained from each subset of m-1 colleges…
Descriptors: Academic Achievement, Bayesian Statistics, College Students, Colleges
Fyans, Leslie J., Jr. – 1978
Unlike the past models guiding cross-cultural psychological research, a new paradigm facilitates multiple level investigations by incorporating both culture-specific (nested) and culture-general (crossed) independent variables within its partially-hierarchical framework. Based upon the generalizability analysis, this model generates sequential…
Descriptors: Analysis of Variance, Bayesian Statistics, Cognitive Processes, Comparative Analysis
Previous Page | Next Page »
Pages: 1 | 2
Direct link
