000			02711nam a22003498i 4500
001			CR9780511973420
003			UkCbUP
005			20200124160256.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			101011s2011||||enk o ||1 0|eng|d
020			_a9780511973420 (ebook)
020			_z9780521198158 (hardback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aQA161.B5 _bH55 2011
082	0	0	_a519.2/4 _222
100	1		_aHilbe, Joseph M., _d1944- _eauthor.
245	1	0	_aNegative binomial regression / _cJoseph M. Hilbe.
250			_aSecond edition.
264		1	_aCambridge : _bCambridge University Press, _c2011.
300			_a1 online resource (xviii, 553 pages) : _bdigital, PDF file(s).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
500			_aTitle from publisher's bibliographic system (viewed on 05 Oct 2015).
505	0		_aThe concept of risk -- Overview of count response models -- Methods of estimation -- Assessment of count models -- Poisson regression -- Overdispersion -- Negative binomial regression -- Negative binomial regression: modeling -- Alternative variance parameterizations -- Problems with zero counts -- Censored and truncated count models -- Handling endogeneity and latent class models -- Count panel models -- Bayesian negative binomial models -- Appendix A. Constructing and interpreting interactions terms -- Appendix B. Data sets, commands, functions.
520			_aThis second edition of Hilbe's Negative Binomial Regression is a substantial enhancement to the popular first edition. The only text devoted entirely to the negative binomial model and its many variations, nearly every model discussed in the literature is addressed. The theoretical and distributional background of each model is discussed, together with examples of their construction, application, interpretation and evaluation. Complete Stata and R codes are provided throughout the text, with additional code (plus SAS), derivations and data provided on the book's website. Written for the practising researcher, the text begins with an examination of risk and rate ratios, and of the estimating algorithms used to model count data. The book then gives an in-depth analysis of Poisson regression and an evaluation of the meaning and nature of overdispersion, followed by a comprehensive analysis of the negative binomial distribution and of its parameterizations into various models for evaluating count data.
650		0	_aNegative binomial distribution.
650		0	_aPoisson algebras.
776	0	8	_iPrint version: _z9780521198158
856	4	0	_uhttps://doi.org/10.1017/CBO9780511973420
999			_c519976 _d519974