Applied regression analysis and other multivariable methods David G. Kleinbaum, Emory University, Lawrence L. Kupper, University of North Carolina, Chapel Hill, Azhar Nizam, Emory University, Eli S. Rosenberg, Emory University.
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TextPublication details: USA ; Cengage Learning ; 2014.Edition: Fifth editionDescription: xix, 1051 pages : illustrations ; 24 cmISBN: - 9781285051086
- 1285051084
- WA900
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PGIM-Academic Centre Main Library | Public Health | WA900 A66 (Browse shelf(Opens below)) | 018195 | Available | 018195 |
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Previous edition: 2008.
Includes bibliographical references and index.
Concepts and examples of research -- Classification of variables and the choice of analysis -- Basic statistics : a review -- Introduction to regression analysis -- Straight-line regression analysis -- Correlation coefficient and straight-line regression analysis -- Analysis-of-variance table -- Multiple regression analysis : general considerations -- Statistical inference in multiple regression -- Correlations : multiple, partial, and multiple partial -- Confounding and interaction in regression -- Dummy variables in regression -- Analysis of covariance and other methods for adjusting continuous data -- Regression diagnostics -- Polynomial regression -- Selecting the best regression equation -- One-way analysis of variance -- Randomized blocks : special case of two-way ANOVA -- Two-way ANOVA with equal cell numbers -- Two-way ANOVA with unequal cell numbers -- Method of maximum likelihood -- Logistic regression analysis -- Polytomous and ordinal logistic regression -- Poisson regression analysis -- Analysis of correlated data part 1 : the general linear mixed method -- Analysis of correlated data part 2 : random effects and other issues -- Sample size planning for linear and logisitc regression and analysis of variance -- Appendix A. Tables -- Appendix B. Matrices and their relationship to regression analysis -- Appendix C. SAS computer appendix -- Appendix D. Answers to selected problems.
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