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Tan, Teck Kiang – Practical Assessment, Research & Evaluation, 2023
Researchers often have hypotheses concerning the state of affairs in the population from which they sampled their data to compare group means. The classical frequentist approach provides one way of carrying out hypothesis testing using ANOVA to state the null hypothesis that there is no difference in the means and proceed with multiple comparisons…
Descriptors: Comparative Analysis, Hypothesis Testing, Statistical Analysis, Guidelines
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Teck Kiang Tan – Practical Assessment, Research & Evaluation, 2024
The procedures of carrying out factorial invariance to validate a construct were well developed to ensure the reliability of the construct that can be used across groups for comparison and analysis, yet mainly restricted to the frequentist approach. This motivates an update to incorporate the growing Bayesian approach for carrying out the Bayesian…
Descriptors: Bayesian Statistics, Factor Analysis, Programming Languages, Reliability
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Boedeker, Peter – Practical Assessment, Research & Evaluation, 2017
Hierarchical linear modeling (HLM) is a useful tool when analyzing data collected from groups. There are many decisions to be made when constructing and estimating a model in HLM including which estimation technique to use. Three of the estimation techniques available when analyzing data with HLM are maximum likelihood, restricted maximum…
Descriptors: Hierarchical Linear Modeling, Maximum Likelihood Statistics, Bayesian Statistics, Computation
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Stone, Clement A.; Tang, Yun – Practical Assessment, Research & Evaluation, 2013
Propensity score applications are often used to evaluate educational program impact. However, various options are available to estimate both propensity scores and construct comparison groups. This study used a student achievement dataset with commonly available covariates to compare different propensity scoring estimation methods (logistic…
Descriptors: Comparative Analysis, Probability, Sample Size, Program Evaluation