Quasi-least squares regression. (2014)

• Record Type: Book
• Further Information: Note: Justine Shults, Joseph M. Hilbe.
• Authors: Shults, Justine; Hilbe, Joseph M, 1944-
• Contents: Introduction; Introduction; When QLS Might Be Considered as an Alternative to GEE; Motivating Studies; Summary Review of Generalized Linear Models; Background; Generalized Linear Models; Generalized Estimating Equations; Application for Obesity Study Provided in Chapter One Quasi-Least Squares Theory and Applications ; History and Theory of QLS Regression; Why QLS Is a "Quasi" Least Squares Approach; The Least-Squares Approach Employed in Stage One of QLS for Estimation of α; Stage-Two QLS Estimates of the Correlation Parameter for the AR(1) Structure; Algorithm for QLS; Other Approaches That Are Based on GEE; Example; Summary Mixed Linear Structures and Familial Data; Notation for Data from Nuclear Families; Familial Correlation Structures for Analysis of Data from Nuclear Families; Other Work on Assessment of Familial Correlations with QLS; Justification of Implementation of QLS for Familial Structures via Consideration of the Class of Mixed Linear Correlation Structures; Demonstration of QLS for Analysis of Balanced Familial Data Using Stata Software; Demonstration of QLS for Analysis of Unbalanced Familial Data Using R Software; Simulations to Compare Implementation of QLS with Correct Specification of the Trio Structure versus Correct Specification with GEE and Incorrect Specification of the Exchangeable Working; Structure with GEE; Summary and Future Research Directions Correlation Structures for Clustered and Longitudinal Data; Characteristics of Clustered and Longitudinal Data; The Exchangeable Correlation Structure for Clustered Data; The Tri-Diagonal Correlation Structure; The AR(1) Structure for Analysis of (Planned) Equally Spaced Longitudinal Data; The Markov Structure for Analysis of Unequally Spaced Longitudinal Data; The Unstructured Matrix for Analysis of Balanced Data; Other Structures; Implementation of QLS for Patterned Correlation Structures; Summary; Appendix Analysis of Data with Multiple Sources of Correlation; Characteristics of Data with Multiple Sources of Correlation; Multi-Source Correlated Data That Are Totally Balanced; Multi-Source Correlated Data That Are Balanced within Clusters; Multi-Source Correlated Data That Are Unbalanced; Asymptotic Relative Efficiency Calculations; Summary; Appendix Correlated Binary Data; Additional Constraints for Binary Data; When Violation of the Prentice Constraints for Binary Data Is Likely to Occur; Implications of Violation of Constraints for Binary Data; Comparison between GEE, QLS, and MARK1ML; Prentice-Corrected QLS and GEE; Summary Assessing Goodness of Fit and Choice of Correlation Structure for QLS and GEE; Simulation Scenarios; Simulation Results; Summary and Recommendations Sample Size and Demonstration; Two-Group Comparisons; More Complex Situations; Worked Example; Discussion and Summary Bibliography Index Exercises appear at the end of each chapter.
• Edition: 1st
• Publisher Details: Boca Raton : Chapman & Hall/CRC
• Publication Date: 2014
• Extent: 1 online resource, illustrations (black and white)
• Subjects: 519.536; Least squares; Generalized estimating equations
• Languages: English
• ISBNs: 9781420099942
• Notes: Note: Description based on CIP data; resource not viewed.
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