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100   $a20020318d2003      uy         0
101 0 $aeng
135   $aur|n|---|||||
181   $ctxt
182   $cc
183   $acr
200 10$aApplied longitudinal data analysis for epidemiology $ea practical guide /$fJos W.R. Twisk
205   $a1st ed.
210   $aCambridge, UK ;$aNew York $cCambridge University Press$d2003
215   $a1 online resource (319 p.)
300   $aDescription based upon print version of record.
311   $a0-521-52580-2 
311   $a0-521-81976-8 
320   $aIncludes bibliographical references (p. 286-294) and index.
327   $aCover; Half-title; Title; Copyright; Dedication; Contents; Preface; Acknowledgements; 1 Introduction; 2 Study design; 3 Continuous outcome variables; 4 Continuous outcome variables - relationships with other variables; 5 Other possibilities for modelling longitudinal data; 6 Dichotomous outcome variables; 7 Categorical and 'count' outcome variables; 8 Longitudinal studies with two measurements: the definition and analysis of change; 9 Analysis of experimental studies; 10 Missing data in longitudinal studies; 11 Tracking; 12 Software for longitudinal data analysis; 13 Sample size calculations
327   $aReferencesIndex
330   $aIn this book the most important techniques available for longitudinal data analysis are discussed, including simple techniques such as the paired t-test and summary statistics, and more sophisticated techniques such as generalised estimating equations and random coefficient analysis. This practical guide is suitable for non-statisticians involved in medical research and epidemiology.
606   $aEpidemiology$xResearch$xStatistical methods
606   $aEpidemiology$vLongitudinal studies
606   $aEpidemiology$xStatistical methods
615  0$aEpidemiology$xResearch$xStatistical methods.
615  0$aEpidemiology
615  0$aEpidemiology$xStatistical methods.
676   $a614.4/07/27
700   $aTwisk$b Jos W. R.$f1962-$01137751
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910825957703321
996   $aApplied longitudinal data analysis for epidemiology$93975636
997   $aUNINA