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Articles 31 - 33 of 33
Full-Text Articles in Physical Sciences and Mathematics
Evaluating The Efficacy Of Conditional Analysis Of Variance Under Heterogeneity And Non-Normality, Yan Wang, Thanh Pham, Diep Nguyen, Eun Sook Kim, Yi-Hsin Chen, Jeffrey Kromrey, Zhiyao Yi, Yue Yin
Evaluating The Efficacy Of Conditional Analysis Of Variance Under Heterogeneity And Non-Normality, Yan Wang, Thanh Pham, Diep Nguyen, Eun Sook Kim, Yi-Hsin Chen, Jeffrey Kromrey, Zhiyao Yi, Yue Yin
Journal of Modern Applied Statistical Methods
A simulation study was conducted to examine the efficacy of conditional analysis of variance (ANOVA) methods where the initial homogeneity of variance screening leads to the choice between the ANOVA F test and robust ANOVA methods. Type I error control and statistical power were investigated under various conditions.
Mixture Models With Grouping Structure: Retail Analytics Applications, Haidar Almohri
Mixture Models With Grouping Structure: Retail Analytics Applications, Haidar Almohri
Wayne State University Dissertations
Growing competitiveness and increasing availability of data is generating tremendous interest in data-driven analytics across industries. In the retail sector, stores need targeted guidance to improve both the efficiency and effectiveness of individual stores based on their specific location, demographics, and environment. We propose an effective data-driven framework for internal benchmarking that can lead to targeted guidance for individual stores. In particular, we propose an objective method for segmenting stores using a model-based clustering technique that accounts for similarity in store performance dynamics. It relies on effective Finite Mixture of Regression (FMR) techniques for carrying out the model-based clustering with …
A Comparison Of Discriminant Function Analysis And Logistic Regression By Categorizing The Incarcerated Mentally Ill, Mona King
Wayne State University Dissertations
Both discriminant function analysis (DFA) and logistic regression (LR) are used to classify subjects into a category/group based upon several explanatory variables (Liong & Foo, 2013). Although the two procedures are generally related, there is no clear advice in the statistical literature on when to use DFA vs. LR, although LR appears to be preferred due to the claim that its underlying assumptions are more easily met (Liong & Foo, 2013). Although DFA and LR use different methods to accomplish their objectives, they can answer the same research questions (Antonogeorgos et al., 2009). This facilitates a practical comparison of their …