Applied regression analysis and other multivariable methods /
by
Kleinbaum, David G [author.]
; Kupper, Lawrence L [author.]
; Nizam, Azhar [author.]
; Rosenberg, Eli S [author.]
.
Material type: 







Item type | Current location | Call number | Copy number | Status | Notes | Date due | Barcode |
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KAMPALA UNIVERSITY, JINJA General Section | QA37K64 2014 (Browse shelf) | C1 | Available | Material available in hard copy | 2020-0094 |
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PZ5.A2495 2001 African American writers / | Q76 .S3594 2013 Invitation to computer science / | QA11.2 .A94 2013 Mathematical excursions | QA37K64 2014 Applied regression analysis and other multivariable methods / | QA 37.2 .J64 2013 Mathematics : | QA39.3 .A939 2014 Basic college mathematics : an applied approach | QA39.3.A939 2014 Basic college mathematics : |
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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