Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 2 |
| Since 2007 (last 20 years) | 4 |
Descriptor
| Bayesian Statistics | 8 |
| Research Design | 8 |
| Sampling | 8 |
| Mathematical Models | 3 |
| Statistical Analysis | 3 |
| Statistical Significance | 3 |
| Decision Making | 2 |
| Educational Research | 2 |
| Hypothesis Testing | 2 |
| Models | 2 |
| Power (Statistics) | 2 |
| More ▼ | |
Source
| Grantee Submission | 2 |
| American Educational Research… | 1 |
| Online Submission | 1 |
| Review of Educational Research | 1 |
Author
Publication Type
| Reports - Research | 6 |
| Journal Articles | 2 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Makela, Susanna; Si, Yajuan; Gelman, Andrew – Grantee Submission, 2018
Cluster sampling is common in survey practice, and the corresponding inference has been predominantly design-based. We develop a Bayesian framework for cluster sampling and account for the design effect in the outcome modeling. We consider a two-stage cluster sampling design where the clusters are first selected with probability proportional to…
Descriptors: Bayesian Statistics, Statistical Inference, Sampling, Probability
Natesan, Prathiba; Hedges, Larry V. – Grantee Submission, 2016
Although immediacy is one of the necessary criteria to show strong evidence of a causal relation in SCDs, no inferential statistical tool is currently used to demonstrate it. We propose a Bayesian unknown change-point model to investigate and quantify immediacy in SCD analysis. Unlike visual analysis that considers only 3-5 observations in…
Descriptors: Bayesian Statistics, Statistical Inference, Research Design, Models
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
Peer reviewedMeyer, Donald L. – American Educational Research Journal, 1974
See TM 501 202-3 and EJ 060 883 for related articles. (MLP)
Descriptors: Bayesian Statistics, Hypothesis Testing, Power (Statistics), Research Design
PDF pending restorationMeyer, Donald L. – 1971
Bayesian statistical methodology and its possible uses in the behavioral sciences are discussed in relation to the solution of problems in both the use and teaching of fundamental statistical methods, including confidence intervals, significance tests, and sampling. The Bayesian model explains these statistical methods and offers a consistent…
Descriptors: Bayesian Statistics, Data Analysis, Decision Making, Mathematical Models
Miller, John K.; Knapp, Thomas R.
The testing of research hypotheses is directly comparable to the dichotomous decision-making of medical diagnosis or jury trials--not ill/ill, or innocent/guilty decisions. There are costs in both kinds of error, type I errors of falsely rejecting a null hypothesis or type II errors of falsely rejecting an alternative hypothesis. It is important…
Descriptors: Bayesian Statistics, Decision Making, Educational Research, Hypothesis Testing
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

Direct link
