Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 1 |
Since 2016 (last 10 years) | 7 |
Since 2006 (last 20 years) | 16 |
Descriptor
Source
Author
Algina, James | 3 |
Barcikowski, Robert S. | 3 |
Becker, Betsy Jane | 3 |
Olejnik, Stephen F. | 3 |
Porter, Kristin E. | 3 |
Robey, Randall R. | 3 |
Anglin, Gary J. | 2 |
Berger, Michael A. | 2 |
Chao, Chun-I | 2 |
Chen, Milton | 2 |
Doreian, Patrick | 2 |
More ▼ |
Publication Type
Audience
Researchers | 247 |
Practitioners | 18 |
Teachers | 10 |
Policymakers | 6 |
Administrators | 5 |
Media Staff | 2 |
Community | 1 |
Students | 1 |
Location
Canada | 7 |
Netherlands | 4 |
Israel | 2 |
United States | 2 |
Australia | 1 |
Austria | 1 |
Brazil | 1 |
Colorado | 1 |
Connecticut | 1 |
Florida | 1 |
Georgia | 1 |
More ▼ |
Laws, Policies, & Programs
Assessments and Surveys
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
Gehlbach, Hunter; Robinson, Carly D. – Journal of Research on Educational Effectiveness, 2018
Like performance-enhancing drugs inflating apparent athletic achievements, several common social science practices contribute to the production of illusory results. In this article, we examine the processes that lead to illusory findings and describe their consequences. We borrow from an approach used increasingly by other disciplines--the norm of…
Descriptors: Educational Research, Research Methodology, Research Reports, 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
Klugkist, Irene; Laudy, Olav; Hoijtink, Herbert – Psychological Methods, 2010
In this article, a Bayesian model selection approach is introduced that can select the best of a set of inequality and equality constrained hypotheses for contingency tables. The hypotheses are presented in terms of cell probabilities allowing researchers to test (in)equality constrained hypotheses in a format that is directly related to the data.…
Descriptors: Bayesian Statistics, Models, Selection, Probability
Kuiper, Rebecca M.; Hoijtink, Herbert – Psychological Methods, 2010
This article discusses comparisons of means using exploratory and confirmatory approaches. Three methods are discussed: hypothesis testing, model selection based on information criteria, and Bayesian model selection. Throughout the article, an example is used to illustrate and evaluate the two approaches and the three methods. We demonstrate that…
Descriptors: Models, Testing, Hypothesis Testing, Probability
Fulmer, Gavin W. – Online Submission, 2010
School accountability decisions based on standardized tests hinge on the degree of alignment of the test with a state's standards. Yet no established criteria were available for judging strength of alignment. Previous studies of alignment among tests, standards, and teachers' instruction have yielded mixed results that are difficult to interpret…
Descriptors: Standardized Tests, Hypothesis Testing, Accountability, Criterion Referenced Tests
Flaherty, Brian P. – Developmental Psychology, 2008
Developmental research often involves studying change across 2 or more processes or constructs simultaneously. A natural question in this work is whether change in these 2 processes is related or independent. Associative latent transition analysis (ALTA) was designed to test hypotheses about the degree to which change in 2 discrete latent…
Descriptors: Hypothesis Testing, Evaluation Methods, Change, Models
Boon, Helen J. – Australian Educational Researcher, 2008
Dropping out of school has been associated with a student's ethnicity, socioeconomic status, challenging behaviours and low academic achievement. This paper describes research conducted with 1050 students aged 12-15, in three North Queensland urban high schools to investigate issues related to Indigenous and non-Indigenous students at risk of…
Descriptors: Low Achievement, Academic Achievement, High Risk Students, Family Structure
Roscoe, Rod D.; Chi, Michelene T. H. – Review of Educational Research, 2007
Prior research has established that peer tutors can benefit academically from their tutoring experiences. However, although tutor learning has been observed across diverse settings, the magnitude of these gains is often underwhelming. In this review, the authors consider how analyses of tutors' actual behaviors may help to account for variation in…
Descriptors: Prior Learning, Tutors, Methods, Training Methods
Ferron, John; Jones, Peggy K. – Journal of Experimental Education, 2006
The authors present a method that ensures control over the Type I error rate for those who visually analyze the data from response-guided multiple-baseline designs. The method can be seen as a modification of visual analysis methods to incorporate a mechanism to control Type I errors or as a modification of randomization test methods to allow…
Descriptors: Multivariate Analysis, Data Analysis, Inferences, Monte Carlo Methods