000			03087nam a22003738i 4500
001			CR9781139342834
003			UkCbUP
005			20200124160306.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			120306s2013||||enk o ||1 0|eng|d
020			_a9781139342834 (ebook)
020			_z9781107030039 (hardback)
020			_z9781107699922 (paperback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aRA652.2.M3 _bT95 2013
082	0	0	_a614.4 _223
100	1		_aTwisk, Jos W. R., _d1962- _eauthor.
245	1	0	_aApplied longitudinal data analysis for epidemiology : _ba practical guide / _cJos W.R. Twisk, Department of Epidemiology and Biostatistics, Medical Center and the Department of Health Sciences of the Vrije Universteit, Amsterdam.
250			_aSecond edition.
264		1	_aCambridge : _bCambridge University Press, _c2013.
300			_a1 online resource (xiv, 321 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	8		_aMachine generated contents note: Preface; Acknowledgements; 1. Introduction; 2. Study design; 3. Continuous outcome variables; 4. Continuous outcome variables - relationships with other variables; 5. The modelling of time; 6. Other possibilities for modelling longitudinal data; 7. Dichotomous outcome variables; 8. Categorical and 'count' outcome variables; 9. Analysis data from experimental studies; 10. Missing data in longitudinal studies; 11. Sample size calculations; 12. Software for longitudinal data analysis; 13. One step further; References; Index.
520			_aThis book discusses the most important techniques available for longitudinal data analysis, from simple techniques such as the paired t-test and summary statistics, to more sophisticated ones such as generalized estimating of equations and mixed model analysis. A distinction is made between longitudinal analysis with continuous, dichotomous and categorical outcome variables. The emphasis of the discussion lies in the interpretation and comparison of the results of the different techniques. The second edition includes new chapters on the role of the time variable and presents new features of longitudinal data analysis. Explanations have been clarified where necessary and several chapters have been completely rewritten. The analysis of data from experimental studies and the problem of missing data in longitudinal studies are discussed. Finally, an extensive overview and comparison of different software packages is provided. This practical guide is essential for non-statisticians and researchers working with longitudinal data from epidemiological and clinical studies.
650		0	_aEpidemiology _xResearch _xStatistical methods.
650		0	_aEpidemiology _vLongitudinal studies.
650		0	_aEpidemiology _xStatistical methods.
776	0	8	_iPrint version: _z9781107030039
856	4	0	_uhttps://doi.org/10.1017/CBO9781139342834
999			_c520747 _d520745