LEADER 03939nam  22007092  450 
001 9910817367003321
005 20220504175400.0
010   $a1-107-06535-6
010   $a1-316-09031-0
010   $a1-107-05691-8
010   $a1-107-05475-3
010   $a1-107-05804-X
010   $a1-107-05931-3
010   $a1-139-34283-5
010   $a1-107-05581-4
035   $a(CKB)2670000000353352
035   $a(EBL)1182964
035   $a(OCoLC)843187582
035   $a(SSID)ssj0000871111
035   $a(PQKBManifestationID)11536628
035   $a(PQKBTitleCode)TC0000871111
035   $a(PQKBWorkID)10821174
035   $a(PQKB)11022344
035   $a(UkCbUP)CR9781139342834
035   $a(MiAaPQ)EBC1182964
035   $a(Au-PeEL)EBL1182964
035   $a(CaPaEBR)ebr10695368
035   $a(CaONFJC)MIL494695
035   $a(PPN)261294695
035   $a(EXLCZ)992670000000353352
100   $a20120306d2013||||  uy|            0
101 0 $aeng
135   $aur|||||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aApplied longitudinal data analysis for epidemiology$b[electronic resource] $ea practical guide /$fJos W.R
205   $aSecond edition.
210  1$aCambridge :$cCambridge University Press,$d2013.
215   $a1 online resource (xiv, 321 pages) $cdigital, PDF file(s)
225 0 $aCambridge medicine Applied longitudinal data analysis for epidemiology
300   $aTitle from publisher's bibliographic system (viewed on 05 Oct 2015).
311   $a1-107-69992-4 
311   $a1-107-03003-X 
320   $aIncludes bibliographical references and index.
327   $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.
330   $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.
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
686   $aMED028000$2bisacsh
700   $aTwisk$b Jos W. R.$f1962-$01137751
801  0$bUkCbUP
801  1$bUkCbUP
906   $aBOOK
912   $a9910817367003321
996   $aApplied longitudinal data analysis for epidemiology$93975636
997   $aUNINA