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Ethan R. Van Norman; David A. Klingbeil; Adelle K. Sturgell – Grantee Submission, 2024
Single-case experimental designs (SCEDs) have been used with increasing frequency to identify evidence-based interventions in education. The purpose of this study was to explore how several procedural characteristics, including within-phase variability (i.e., measurement error), number of baseline observations, and number of intervention…
Descriptors: Research Design, Case Studies, Effect Size, Error of Measurement
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Victoria Savalei; Yves Rosseel – Structural Equation Modeling: A Multidisciplinary Journal, 2022
This article provides an overview of different computational options for inference following normal theory maximum likelihood (ML) estimation in structural equation modeling (SEM) with incomplete normal and nonnormal data. Complete data are covered as a special case. These computational options include whether the information matrix is observed or…
Descriptors: Structural Equation Models, Computation, Error of Measurement, Robustness (Statistics)
Eli Ben-Michael; Avi Feller; Erin Hartman – Grantee Submission, 2023
In the November 2016 U.S. presidential election, many state level public opinion polls, particularly in the Upper Midwest, incorrectly predicted the winning candidate. One leading explanation for this polling miss is that the precipitous decline in traditional polling response rates led to greater reliance on statistical methods to adjust for the…
Descriptors: Public Opinion, National Surveys, Elections, Political Campaigns
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Breen, Richard; Bernt Karlson, Kristian; Holm, Anders – Sociological Methods & Research, 2021
The Karlson-Holm-Breen (KHB) method has rapidly become popular as a way of separating the impact of confounding from rescaling when comparing conditional and unconditional parameter estimates in nonlinear probability models such as the logit and probit. In this note, we show that the same estimates can be obtained in a somewhat different way to…
Descriptors: Probability, Models, Computation, Comparative Analysis
Ben-Michael, Eli; Feller, Avi; Rothstein, Jesse – Grantee Submission, 2022
Staggered adoption of policies by different units at different times creates promising opportunities for observational causal inference. Estimation remains challenging, however, and common regression methods can give misleading results. A promising alternative is the synthetic control method (SCM), which finds a weighted average of control units…
Descriptors: Causal Models, Statistical Inference, Computation, Evaluation Methods
Pashley, Nicole E.; Miratrix, Luke W. – Journal of Educational and Behavioral Statistics, 2021
Evaluating blocked randomized experiments from a potential outcomes perspective has two primary branches of work. The first focuses on larger blocks, with multiple treatment and control units in each block. The second focuses on matched pairs, with a single treatment and control unit in each block. These literatures not only provide different…
Descriptors: Causal Models, Statistical Inference, Research Methodology, Computation
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Mansolf, Maxwell; Jorgensen, Terrence D.; Enders, Craig K. – Grantee Submission, 2020
Structural equation modeling (SEM) applications routinely employ a trilogy of significance tests that includes the likelihood ratio test, Wald test, and score test or modification index. Researchers use these tests to assess global model fit, evaluate whether individual estimates differ from zero, and identify potential sources of local misfit,…
Descriptors: Structural Equation Models, Computation, Scores, Simulation
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Vegetabile, Brian G.; Stout-Oswald, Stephanie A.; Davis, Elysia Poggi; Baram, Tallie Z.; Stern, Hal S. – Journal of Educational and Behavioral Statistics, 2019
Predictability of behavior is an important characteristic in many fields including biology, medicine, marketing, and education. When a sequence of actions performed by an individual can be modeled as a stationary time-homogeneous Markov chain the predictability of the individual's behavior can be quantified by the entropy rate of the process. This…
Descriptors: Markov Processes, Prediction, Behavior, Computation
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Walters, Glenn D. – International Journal of Social Research Methodology, 2019
Identifying mediators in variable chains as part of a causal mediation analysis can shed light on issues of causation, assessment, and intervention. However, coefficients and effect sizes in a causal mediation analysis are nearly always small. This can lead those less familiar with the approach to reject the results of causal mediation analysis.…
Descriptors: Effect Size, Statistical Analysis, Sampling, Statistical Inference
Oranje, Andreas; Kolstad, Andrew – Journal of Educational and Behavioral Statistics, 2019
The design and psychometric methodology of the National Assessment of Educational Progress (NAEP) is constantly evolving to meet the changing interests and demands stemming from a rapidly shifting educational landscape. NAEP has been built on strong research foundations that include conducting extensive evaluations and comparisons before new…
Descriptors: National Competency Tests, Psychometrics, Statistical Analysis, Computation
Pashley, Nicole E.; Miratrix, Luke W. – Grantee Submission, 2019
In the causal inference literature, evaluating blocking from a potential outcomes perspective has two main branches of work. The first focuses on larger blocks, with multiple treatment and control units in each block. The second focuses on matched pairs, with a single treatment and control unit in each block. These literatures not only provide…
Descriptors: Causal Models, Statistical Inference, Research Methodology, Computation
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Chung, Seungwon; Cai, Li – Grantee Submission, 2019
The use of item responses from questionnaire data is ubiquitous in social science research. One side effect of using such data is that researchers must often account for item level missingness. Multiple imputation (Rubin, 1987) is one of the most widely used missing data handling techniques. The traditional multiple imputation approach in…
Descriptors: Computation, Statistical Inference, Structural Equation Models, Goodness of Fit
Qin, Xu; Hong, Guanglei – Journal of Educational and Behavioral Statistics, 2017
When a multisite randomized trial reveals between-site variation in program impact, methods are needed for further investigating heterogeneous mediation mechanisms across the sites. We conceptualize and identify a joint distribution of site-specific direct and indirect effects under the potential outcomes framework. A method-of-moments procedure…
Descriptors: Randomized Controlled Trials, Hierarchical Linear Modeling, Statistical Analysis, Probability
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Valente, Matthew J.; Gonzalez, Oscar; Miocevic, Milica; MacKinnon, David P. – Educational and Psychological Measurement, 2016
Methods to assess the significance of mediated effects in education and the social sciences are well studied and fall into two categories: single sample methods and computer-intensive methods. A popular single sample method to detect the significance of the mediated effect is the test of joint significance, and a popular computer-intensive method…
Descriptors: Structural Equation Models, Sampling, Statistical Inference, Statistical Bias
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Dogan, C. Deha – Eurasian Journal of Educational Research, 2017
Background: Most of the studies in academic journals use p values to represent statistical significance. However, this is not a good indicator of practical significance. Although confidence intervals provide information about the precision of point estimation, they are, unfortunately, rarely used. The infrequent use of confidence intervals might…
Descriptors: Sampling, Statistical Inference, Periodicals, Intervals
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