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Showing 1 to 15 of 17 results Save | Export
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Weicong Lyu; Peter M. Steiner – Society for Research on Educational Effectiveness, 2021
Doubly robust (DR) estimators that combine regression adjustments and inverse probability weighting (IPW) are widely used in causal inference with observational data because they are claimed to be consistent when either the outcome or the treatment selection model is correctly specified (Scharfstein et al., 1999). This property of "double…
Descriptors: Robustness (Statistics), Causal Models, Statistical Inference, Regression (Statistics)
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Amy Shelton; Collin Hitt – Journal of School Choice, 2024
There are over one million school-age children in Missouri, and we estimate 61,000 (6% of all school-age children) are homeschooled. Missouri is one of 29 states that does not require homeschooling to be reported. Using methods that can be replicated elsewhere with publicly available data, we test three approaches to estimating homeschool…
Descriptors: Home Schooling, Attendance, Data Collection, School Statistics
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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
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Levy, Roy – Educational Measurement: Issues and Practice, 2020
In this digital ITEMS module, Dr. Roy Levy describes Bayesian approaches to psychometric modeling. He discusses how Bayesian inference is a mechanism for reasoning in a probability-modeling framework and is well-suited to core problems in educational measurement: reasoning from student performances on an assessment to make inferences about their…
Descriptors: Bayesian Statistics, Psychometrics, Item Response Theory, Statistical Inference
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Blackwell, Matthew; Honaker, James; King, Gary – Sociological Methods & Research, 2017
We extend a unified and easy-to-use approach to measurement error and missing data. In our companion article, Blackwell, Honaker, and King give an intuitive overview of the new technique, along with practical suggestions and empirical applications. Here, we offer more precise technical details, more sophisticated measurement error model…
Descriptors: Error of Measurement, Correlation, Simulation, Bayesian Statistics
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Coffman, Donna L. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
Mediation is usually assessed by a regression-based or structural equation modeling (SEM) approach that we refer to as the classical approach. This approach relies on the assumption that there are no confounders that influence both the mediator, "M", and the outcome, "Y". This assumption holds if individuals are randomly…
Descriptors: Structural Equation Models, Simulation, Regression (Statistics), Probability
Coughlin, Mary Ann; Pagano, Marian – 1997
This monograph covers the theory, application, and interpretation of both descriptive and inferential statistical techniques in institutional research. Each chapter opens with a hypothetical case study, which is used to illustrate the application of one or more statistical procedures to typical research questions. Chapter 2 covers the comparison…
Descriptors: Analysis of Covariance, Analysis of Variance, Chi Square, Correlation
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Maeshiro, Asatoshi – Journal of Economic Education, 1996
Rectifies the unsatisfactory textbook treatment of the finite-sample proprieties of estimators of regression models with a lagged dependent variable and autocorrelated disturbances. Maintains that the bias of the ordinary least squares estimator is determined by the dynamic and correlation effects. (MJP)
Descriptors: Causal Models, Correlation, Economics Education, Heuristics
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Sotos, Ana Elisa Castro; Vanhoof, Stijn; Van den Noortgate, Wim; Onghena, Patrick – Educational Research Review, 2007
A solid understanding of "inferential statistics" is of major importance for designing and interpreting empirical results in any scientific discipline. However, students are prone to many misconceptions regarding this topic. This article structurally summarizes and describes these misconceptions by presenting a systematic review of publications…
Descriptors: Research Needs, Research Methodology, Statistical Inference, Statistics
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Keller, Clayton E.; And Others – Remedial and Special Education (RASE), 1987
In rebuttal to a critique of the authors' examination of prevalence rate variability for special education categories, it is claimed that a consideration of the nature of prevalence rate data, the correct use of inferential statistics, and the coefficient of variation itself, suggest the objections are not justified. (Author/DB)
Descriptors: Disabilities, Incidence, Research Methodology, Statistical Analysis
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Da Prato, Robert A. – Topics in Early Childhood Special Education, 1992
This paper argues that judgment-based assessment of data from multiply replicated single-subject or small-N studies should replace normative-based (p=less than 0.05) assessment of large-N research in the clinical sciences, and asserts that inferential statistics should be abandoned as a method of evaluating clinical research data. (Author/JDD)
Descriptors: Evaluation Methods, Evaluative Thinking, Norms, Research Design
Levy, Roy; Mislevy, Robert J. – US Department of Education, 2004
The challenges of modeling students' performance in simulation-based assessments include accounting for multiple aspects of knowledge and skill that arise in different situations and the conditional dependencies among multiple aspects of performance in a complex assessment. This paper describes a Bayesian approach to modeling and estimating…
Descriptors: Probability, Markov Processes, Monte Carlo Methods, Bayesian Statistics
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Bookstein, Abraham; Podet, Eve B. – Library Quarterly, 1986
Three versions of a probabilistic model adapted from the theory of information retrieval--a binary version, a version using the full value of the data, and a version using principal components--were tested and applied to data available from application forms to predict graduate school performance of library school students. (EM)
Descriptors: Academic Achievement, Grade Point Average, Graduate Students, Higher Education
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Burrell, Quentin L. – Journal of Documentation, 1987
Describes a circulation model for academic research libraries which uses the mixed Poisson model, incorporating ageing of library materials, to predict future use of monographs and to suggest weeding procedures based on frequency of circulation. Longitudinal studies are examined and statistical details are appended. (Author/LRW)
Descriptors: Academic Libraries, Graphs, Higher Education, Library Circulation
Sandler, Andrew B. – 1987
Statistical significance is misused in educational and psychological research when it is applied as a method to establish the reliability of research results. Other techniques have been developed which can be correctly utilized to establish the generalizability of findings. Methods that do provide such estimates are known as invariance or…
Descriptors: Analysis of Covariance, Analysis of Variance, Correlation, Discriminant Analysis
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