Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 1 |
Since 2016 (last 10 years) | 6 |
Since 2006 (last 20 years) | 7 |
Descriptor
Source
Author
Publication Type
Reports - Research | 16 |
Speeches/Meeting Papers | 12 |
Journal Articles | 9 |
Guides - Non-Classroom | 5 |
Opinion Papers | 3 |
Reports - Evaluative | 2 |
Information Analyses | 1 |
Reports - Descriptive | 1 |
Tests/Questionnaires | 1 |
Education Level
High Schools | 1 |
Secondary Education | 1 |
Audience
Researchers | 27 |
Teachers | 2 |
Policymakers | 1 |
Practitioners | 1 |
Location
Minnesota | 1 |
Laws, Policies, & Programs
Assessments and Surveys
Gates MacGinitie Reading Tests | 1 |
What Works Clearinghouse Rating
Deke, John; Finucane, Mariel; Thal, Daniel – National Center for Education Evaluation and Regional Assistance, 2022
BASIE is a framework for interpreting impact estimates from evaluations. It is an alternative to null hypothesis significance testing. This guide walks researchers through the key steps of applying BASIE, including selecting prior evidence, reporting impact estimates, interpreting impact estimates, and conducting sensitivity analyses. The guide…
Descriptors: Bayesian Statistics, Educational Research, Data Interpretation, Hypothesis Testing
Porter, Kristin E. – Journal of Research on Educational Effectiveness, 2018
Researchers are often interested in testing the effectiveness of an intervention on multiple outcomes, for multiple subgroups, at multiple points in time, or across multiple treatment groups. The resulting multiplicity of statistical hypothesis tests can lead to spurious findings of effects. Multiple testing procedures (MTPs) are statistical…
Descriptors: Statistical Analysis, Program Effectiveness, Intervention, Hypothesis Testing
Hicks, Tyler; Rodríguez-Campos, Liliana; Choi, Jeong Hoon – American Journal of Evaluation, 2018
To begin statistical analysis, Bayesians quantify their confidence in modeling hypotheses with priors. A prior describes the probability of a certain modeling hypothesis apart from the data. Bayesians should be able to defend their choice of prior to a skeptical audience. Collaboration between evaluators and stakeholders could make their choices…
Descriptors: Bayesian Statistics, Evaluation Methods, Statistical Analysis, Hypothesis Testing
Porter, Kristin E. – Grantee Submission, 2017
Researchers are often interested in testing the effectiveness of an intervention on multiple outcomes, for multiple subgroups, at multiple points in time, or across multiple treatment groups. The resulting multiplicity of statistical hypothesis tests can lead to spurious findings of effects. Multiple testing procedures (MTPs) are statistical…
Descriptors: Statistical Analysis, Program Effectiveness, Intervention, Hypothesis Testing
Porter, Kristin E. – MDRC, 2016
In education research and in many other fields, researchers are often interested in testing the effectiveness of an intervention on multiple outcomes, for multiple subgroups, at multiple points in time, or across multiple treatment groups. The resulting multiplicity of statistical hypothesis tests can lead to spurious findings of effects. Multiple…
Descriptors: Statistical Analysis, Program Effectiveness, Intervention, Hypothesis Testing
Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S. – Grantee Submission, 2016
A commonly held belief among educators, researchers, and students is that high-quality texts are easier to read than low-quality texts, as they contain more engaging narrative and story-like elements. Interestingly, these assumptions have typically failed to be supported by the literature on writing. Previous research suggests that higher quality…
Descriptors: Role, Writing (Composition), Natural Language Processing, Hypothesis Testing
Preacher, Kristopher J.; Zyphur, Michael J.; Zhang, Zhen – Psychological Methods, 2010
Several methods for testing mediation hypotheses with 2-level nested data have been proposed by researchers using a multilevel modeling (MLM) paradigm. However, these MLM approaches do not accommodate mediation pathways with Level-2 outcomes and may produce conflated estimates of between- and within-level components of indirect effects. Moreover,…
Descriptors: Structural Equation Models, Hypothesis Testing, Statistical Analysis, Predictor Variables

Seaman, Samuel; And Others – 1984
The probability of obtaining a significant statistic, using the parametric analysis of covariance (ANCOVA) and the rank transform ANCOVA, was estimated for three conditions defined in terms of conditional distributions for two groups. The distributions were both normal, both skewed in the same direction but to different degrees, or both skewed to…
Descriptors: Analysis of Covariance, Correlation, Hypothesis Testing, Probability

Wolfle, Lee M.; Ethington, Corinna A. – 1984
In his early exposition of path analysis, Duncan (1966) noted that the method "provides a calculus for indirect effects." Despite the interest in indirect causal effects, most users treat them as if they are population parameters and do not test whether they are statistically significant. Sobel (1982) has recently derived the asymptotic…
Descriptors: Algorithms, Computer Software, Hypothesis Testing, Path Analysis

Daskin, Alan J. – Journal of Economic Education, 1992
Considers counterintuitive propositions about using point elasticities to estimate quantity changes in response to price changes. Suggests that elasticity increases with price along a linear demand curve, but falling quantity demand offsets it. Argues that point elasticity with finite percentage change in price only approximates percentage change…
Descriptors: Costs, Economic Research, Economics, Higher Education

Hertzog, Christopher; Rovine, Michael – Child Development, 1985
Attempts to distill a growing technical literature on repeated-measures analysis of variance into a few simple principles for selecting an analytic technique. Argues that researchers ought not opt for a general analysis strategy when current computer technology makes it possible to select the optimal analysis technique for a given data set. (RH)
Descriptors: Analysis of Variance, Computer Software, Developmental Psychology, Hypothesis Testing

McClure, John; Suen, Hoi K. – Topics in Early Childhood Special Education, 1994
This article compares three models that have been the foundation for approaches to the analysis of statistical significance in early childhood research--the Fisherian and the Neyman-Pearson models (both considered "classical" approaches), and the Bayesian model. The article concludes that all three models have a place in the analysis of research…
Descriptors: Bayesian Statistics, Early Childhood Education, Educational Research, Hypothesis Testing
Coovert, Michael D.; And Others – 1988
Arguing that sufficient theory exists about the interplay between human information processing, computer systems, and the demands of various tasks to construct useful theories of human-computer interaction, this study presents a structural model of human-computer interaction and reports the results of various statistical analyses of this model.…
Descriptors: Computers, Decision Making, Hypothesis Testing, Intelligence
Miller, Michael K.; Farmer, Frank L. – 1986
Theories employed to explain regularities in social behavior often contain explicit or implicit reference to the presence of nonlinear and/or nonadditive (i.e., multiplicative) relationships among germane variables. While such nonadditive features are theoretically important, the inclusion of quadratic or multiplicative terms in structural…
Descriptors: Data Analysis, Hypothesis Testing, Interaction, Models

Rushinek, Avi; Rushinek, Sara F. – Information Processing and Management, 1986
This study used multiple regression analysis to relate computer user satisfaction to communication monitor (CM) variables. Results indicate the variables of user expectations, manufacturers, and vendors are most significant in affecting overall satisfaction, whereas number of systems represented and not using communication monitors have least…
Descriptors: Communications, Computer Software, Expectation, Hypothesis Testing
Previous Page | Next Page »
Pages: 1 | 2