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Full-Text Articles in Applied Statistics
Constructing Confidence Intervals For Effect Sizes In Anova Designs, Li-Ting Chen, Chao-Ying Joanne Peng
Constructing Confidence Intervals For Effect Sizes In Anova Designs, Li-Ting Chen, Chao-Ying Joanne Peng
Journal of Modern Applied Statistical Methods
A confidence interval for effect sizes provides a range of plausible population effect sizes (ES) that are consistent with data. This article defines an ES as a standardized linear contrast of means. The noncentral method, Bonett’s method, and the bias-corrected and accelerated bootstrap method are illustrated for constructing the confidence interval for such an effect size. Results obtained from the three methods are discussed and interpretations of results are offered.
Bootstrap Interval Estimation Of Reliability Via Coefficient Omega, Miguel A. Padilla, Jasmin Divers
Bootstrap Interval Estimation Of Reliability Via Coefficient Omega, Miguel A. Padilla, Jasmin Divers
Journal of Modern Applied Statistical Methods
Three different bootstrap confidence intervals (CIs) for coefficient omega were investigated. The CIs were assessed through a simulation study with conditions not previously investigated. All methods performed well; however, the normal theory bootstrap (NTB) CI had the best performance because it had more consistent acceptable coverage under the simulation conditions investigated.
Theory And Methods For Gini Coefficients Partitioned By Quantile Range, Chaitra Nagaraja
Theory And Methods For Gini Coefficients Partitioned By Quantile Range, Chaitra Nagaraja
Chaitra H Nagaraja
The Gini coefficient is frequently used to measure inequality in populations. However, it is possible that inequality levels may change over time differently for disparate subgroups which cannot be detected with population-level estimates only. Therefore, it may be informative to examine inequality separately for these segments. The case where the population is split into two segments based on non-overlapping quantile ranges is examined. Asymptotic theory is derived and practical methods to estimate standard errors and construct confidence intervals using resampling methods are developed. An application to per capita income across census tracts using American Community Survey data is considered.