Applied logistic regression

Forsideomslag
Wiley, 1989 - 307 sider
1 Anmeldelse
From the reviews of the First Edition. "An interesting, useful, and well-written book on logistic regression models . . . Hosmer and Lemeshow have used very little mathematics, have presented difficult concepts heuristically and through illustrative examples, and have included references." -Choice "Well written, clearly organized, and comprehensive . . . the authors carefully walk the reader through the estimation of interpretation of coefficients from a wide variety of logistic regression models . . . their careful explication of the quantitative re-expression of coefficients from these various models is excellent." -Contemporary Sociology "An extremely well-written book that will certainly prove an invaluable acquisition to the practicing statistician who finds other literature on analysis of discrete data hard to follow or heavily theoretical." -The Statistician In this revised and updated edition of their popular book, David Hosmer and Stanley Lemeshow continue to provide an amazingly accessible introduction to the logistic regression model while incorporating advances of the last decade, including a variety of software packages for the analysis of data sets. Hosmer and Lemeshow extend the discussion from biostatistics and epidemiology to cutting-edge applications in data mining and machine learning, guiding readers step-by-step through the use of modeling techniques for dichotomous data in diverse fields. Ample new topics and expanded discussions of existing material are accompanied by a wealth of real-world examples-with extensive data sets available over the Internet.

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LibraryThing Review

Brugeranmeldelse  - bluetyson - LibraryThing

A good book that certainly has practical application. It details the rise in use of this particular technique, and where it is applicable. Also details multiple varieties including multinomial and others. This is definitely a mathematics text that is worth the time to take a look at. Læs hele anmeldelsen

Indhold

Introduction to the Logistic Regression Model
1
The Multiple Logistic Regression Model 2 5
25
Interpretation of the Coefficients of
38
Copyright

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Almindelige termer og sætninger

analysis assess best subsets calculated Chapter chi-square coding computed confidence interval confounder covariate patterns data set degrees of freedom denote design variables DETC deviance diagnostic statistics dichotomous variable distribution equation Error Coeff./SE estimated coefficients estimated logistic probabilities estimated logistic regression estimated odds ratio estimated probabilities estimated standard errors example fitted model fitted values given in Table goodness-of-fit independent variable interaction term leverage likelihood function likelihood ratio test linear regression log odds log-likelihood log-odds ratio logistic regression coefficients logistic regression model logistic regression software logit difference logit model low birth weight main effects matched design matrix maximum likelihood estimates method model containing multivariate model obtained outcome variable p-value parameters plot polytomous quartile regression program residual results of fitting risk factor sample saturated model scale shown in Table significance slope coefficients SMOKE step stepwise stratum subjects univariate variance versus Wald statistics Wald test weighted least squares zero

Henvisninger til denne bog

Om forfatteren (1989)

David W. Hosmer, PhD, is Professor Emeritus of Biostatistics in the School of Public Health and Heatlth Sciences at the University of Massachusetts Amherst. Dr. Hosmer is the coauthor of "Applied Logistic Regression," published by Wiley.

Stanley Lemeshow, PhD, is Professor and Dean of the College of Public Health at The Ohio State University. Dr. Lemeshow has over thirty-five years of academic experience in the areas of regression, categorical data methods, and sampling methods. He is the coauthor of "Sampling of Population: Methods and Application" and "Applied Logistic Regression," both published by Wiley.

Susanne May, PhD, is Assistant Professor of Biostatistics at the University of California, San Diego. Dr. May has over twelve years of experience in providing statistical support for health-related research projects.

PAUL S. LEVY is Professor of Epidemiology and Biostatistics at the University of Illinois School of Public Health. He is a Fellow of both the American Statistical Association and the American College of Epidemiology and has been widely published during his long and distinguished career as a statistician and epidemiologist. Most recently he served as section editor for design of experiments and sample surveys of the Encyclopedia of Biostatistics.
STANLEY LEMESHOW is Professor of Biostatistics in the School of Public Health at the University of Massachusetts at Amherst. He is a Fellow of the American Statistical Association and has published numerous articles in statistical and biomedical journals. In addition to this book, he has coauthored Applied Logistic Regression (Wiley), Adequacy of Sample Size in Health Studies, and Applied Survival Analysis (Wiley).

Bibliografiske oplysninger

QR code for Applied logistic regression
TitelApplied logistic regression
Wiley series in probability and mathematical statistics: Applied probability and statistics
Probability and Statistics Series
Wiley Series in Probability & Mathematical Statistics
ForfattereDavid W. Hosmer, Stanley Lemeshow
BidragyderStanley Lemeshow
UdgiverWiley, 1989
Oprindeligt fraUniversity of Michigan
Digitaliseret24. jul 2008
ISBN0471615536, 9780471615538
Længde307 sider
  
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