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Mathematical statistics --- Latent variables --- Structural equation modeling --- Latent structure analysis. --- Latent variables. --- Structural equation modeling. --- SEM (Structural equation modeling) --- Multivariate analysis --- Factor analysis --- Regression analysis --- Path analysis (Statistics) --- Constructs, Hypothetical --- Hypothetical constructs --- Variables, Latent --- Latent structure analysis --- Variables (Mathematics) --- Correlation (Statistics)

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"The text does an outstanding job of providing the necessary mechanics and theory of the S language. I will use this book in every such course that I teach from this point on." 						 JEFF GILL, University of Florida, Gainesville "The book provides a valuable supplement to texts on regression analysis and linear models by showing readers how to put into practice the strategies and techniques involved in modern statistical methodology. It explains clearly the use of a very sophisticated and powerful statistical software system. And, while the examples and objectives are focused closely on regression and related techniques, the discussion successfully conveys general advice and principles for statistical computing with the S system." 					 WILLIAM JACOBY, University of South Carolina Features: Various facilities of S are introduced as needed within the context of detailed examples Cumulative examples: later examples often depend upon earlier ones, but examples in separate chapters are always independent of each other Asterisks note more demanding material that may be skipped without loss of continuity Boxes explain and highlight the many small differences between S-PLUS and R, and between S3 and S4, so that the reader can quickly locate the material that is relevant to their version of S or skip that information A companion Web site, featuring: instructions for downloading, installing, and using the Windows version of R; add-on packages; versions of the car (companion to applied regression) library that includes the software and data sets described in the book; an appendix for various extensions of regression analysis not covered in the text; and downloadable scripts for all of the examples in the text "If you want to keep up with the latest developments in statistics, you need to use the computer language S. If you want to learn S, there isn't a better way to get started than Fox's An R and S-Plus Companion to Applied Regressio

Computer. Automation --- Mathematical statistics --- regressie-analyse --- wiskundige statistiek --- Regression analysis --- R (Computer program language) --- -R (Computer program language) --- 519.536 --- GNU-S (Computer program language) --- Domain-specific programming languages --- Analysis, Regression --- Linear regression --- Regression modeling --- Multivariate analysis --- Structural equation modeling --- Data processing. --- Data processing --- S-Plus. --- SPlus --- R (Computer program language).

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Mathematical statistics --- Bayesian statistical decision theory --- Nonparametric statistics --- Regression Analysis --- 519.226 --- Bayesian statistical decision theory. --- Regression analysis --- Analysis, Regression --- Linear regression --- Regression modeling --- Multivariate analysis --- Structural equation modeling --- Distribution-free statistics --- Statistics, Distribution-free --- Statistics, Nonparametric --- Bayes' solution --- Bayesian analysis --- Statistical decision --- Inference and decision theory. Likelihood. Bayesian theory. Fiducial probability --- Nonparametric statistics. --- Regression analysis. --- 519.226 Inference and decision theory. Likelihood. Bayesian theory. Fiducial probability --- Statistique

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* Contains additional discussion and examples on left truncation as well as material on more general censoring and truncation patterns. * Introduces the martingale and counting process formulation swil lbe in a new chapter. * Develops multivariate failure time data in a separate chapter and extends the material on Markov and semi Markov formulations. * Presents new examples and applications of data analysis.

Mathematical statistics --- QA 276 .K215 Mathematical statistics --- Failure time data analysis --- Survival analysis (Biometry) --- Regression analysis --- AA / International- internationaal --- 303.0 --- 304.0 --- 519.5 --- Analysis, Regression --- Linear regression --- Regression modeling --- Multivariate analysis --- Structural equation modeling --- Analysis, Survival (Biometry) --- Survivorship analysis (Biometry) --- Biometry --- Analysis, Failure time data --- Data analysis, Failure time --- Failure analysis (Engineering) --- Competing risks --- Statistische technieken in econometrie. Wiskundige statistiek (algemene werken en handboeken). --- Zuivere statistische analyse (algemene naslagwerken). Tijdreeksen. --- Failure time data analysis. --- Regression analysis. --- Survival analysis (Biometry). --- Statistische technieken in econometrie. Wiskundige statistiek (algemene werken en handboeken) --- Zuivere statistische analyse (algemene naslagwerken). Tijdreeksen

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This is the second edition of this text on logistic regression methods, ori- nally published in 1994. As in the first edition, each chapter contains a presentation of its topic in “lecture-book” format together with objectives, an outline, key formulae, practice exercises, and a test. The “lecture-book” has a sequence of illust- tions and formulae in the left column of each page and a script (i.e., text) in the right column. This format allows you to read the script in conjunction with the illustrations and formulae that highlight the main points, formulae, or examples being presented. This second edition has expanded the first edition by adding five new ch- ters and a new appendix. The five new chapters are Chapter 9. Polytomous Logistic Regression Chapter 10. Ordinal Logistic Regression Chapter 11. Logistic Regression for Correlated Data: GEE Chapter 12. GEE Examples Chapter 13. Other Approaches for Analysis of Correlated Data Chapters 9 and 10 extend logistic regression to response variables that have more than two categories. Chapters 11–13 extend logistic regression to gen- alized estimating equations (GEE) and other methods for analyzing cor- lated response data. The appendix is titled “Computer Programs for Logistic Regression” and p- vides descriptions and examples of computer programs for carrying out the variety of logistic regression procedures described in the main text. The so- ware packages considered are SAS Version 8.0, SPSS Version 10.0, and STATA Version 7.0.

Biomathematics. Biometry. Biostatistics --- Mathematical statistics --- Medicine --- Regression analysis. --- Logistic distribution. --- Médecine --- Analyse de régression --- Research --- Statistical methods. --- Recherche --- Méthodes statistiques --- Regression analysis --- Logistic distribution --- Statistical methods --- Electronic books. -- local. --- Medicine -- Research -- Statistical methods. --- Biometry --- Regression Analysis --- Models, Statistical --- Statistics as Topic --- Models, Theoretical --- Epidemiologic Measurements --- Health Care Evaluation Mechanisms --- Investigative Techniques --- Epidemiologic Methods --- Public Health --- Quality of Health Care --- Environment and Public Health --- Analytical, Diagnostic and Therapeutic Techniques and Equipment --- Health Care Quality, Access, and Evaluation --- Health Care --- Medical Research --- Health & Biological Sciences --- -Regression analysis --- #PBIB:2004.3 --- Distribution (Probability theory) --- Analysis, Regression --- Linear regression --- Regression modeling --- Multivariate analysis --- Structural equation modeling --- Clinical sciences --- Medical profession --- Human biology --- Life sciences --- Medical sciences --- Pathology --- Physicians --- -Statistical methods --- Médecine --- Analyse de régression --- Méthodes statistiques --- EPUB-LIV-FT SPRINGER-B --- Statistics. --- Epidemiology. --- Statistics for Life Sciences, Medicine, Health Sciences. --- Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law. --- Statistics for Social Science, Behavioral Science, Education, Public Policy, and Law. --- Research&delete& --- Statistics for Social Sciences, Humanities, Law. --- Health Workforce --- Logistic regression analysis. --- Statistics . --- Statistical analysis --- Statistical data --- Statistical science --- Mathematics --- Econometrics --- Diseases --- Public health --- Medicine - Research - Statistical methods --- Acqui 2006