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020 _a9783031624278
_9978-3-031-62427-8
024 7 _a10.1007/978-3-031-62427-8
_2doi
050 4 _aQA276-280
072 7 _aPBT
_2bicssc
072 7 _aMAT029000
_2bisacsh
072 7 _aPBT
_2thema
100 1 _aWilson, Jeffrey R.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_984319
245 1 0 _aModeling Binary Correlated Responses
_h[electronic resource] :
_bUsing SAS, SPSS, R and STATA /
_cby Jeffrey R. Wilson, Kent A. Lorenz, Lori P. Selby.
250 _a2nd ed. 2024.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2024.
300 _aXXV, 282 p. 28 illus., 21 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aICSA Book Series in Statistics,
_x2199-0999
505 0 _aIntroduction to Binary logistic Regression -- Growth of the Logistic Regression Model -- Standard Binary Logistic Regression Model -- Overdispersed Logistic Regression Model -- Weighted Logistic Regression Model -- Generalized Estimating Equations Logistic Regression -- Generalized Method of Moments logistic regression Model -- Exact Logistic Regression Model -- Two-Level Nested Logistic Regression Model -- Hierarchical Logistic Regression models -- Fixed Effects Logistic Regression Model -- Heteroscedastic Logistic Regression Model.
520 _aThis book is an updated edition of Modeling Binary Correlated Responses Using SAS, SPSS and R, and now it includes the use of STATA. It uses these Statistical tools to analyze correlated binary data, accessible to practitioners in a single volume. Chapters cover recently developed statistical tools and statistical packages, as well as showcase both traditional and new methods for application to health-related research. Data analysis presented in each chapter will provide step-by-step instructions so these new methods can be readily applied to projects. Short tutorials are in the appendix, for readers interested in learning more about the languages. Data and computer programs will be publicly available in order for readers to replicate model development, but learning a new statistical language is not necessary with this book. The inclusion of code for R, SAS, SPSS and STATA, allows for easy implementation by readers. Researchers and graduate students in Statistics, Epidemiology, and Public Health will find this book particularly useful.
650 0 _aStatistics.
_965982
650 0 _aBiometry.
_965981
650 1 4 _aStatistical Theory and Methods.
650 2 4 _aBiostatistics.
_965985
700 1 _aLorenz, Kent A.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_984320
700 1 _aSelby, Lori P.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_984321
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031624261
776 0 8 _iPrinted edition:
_z9783031624285
776 0 8 _iPrinted edition:
_z9783031624292
830 0 _aICSA Book Series in Statistics,
_x2199-0999
_980221
856 4 0 _uhttps://doi.org/10.1007/978-3-031-62427-8
912 _aZDB-2-SMA
912 _aZDB-2-SXMS
999 _c63390
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