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100 1 a| Twisk, Jos W. R.,d| 1962-=| ^A938124;

245 10 a| Applied longitudinal data analysis for epidemiology :b| a practical guide /c| Jos W.R. Twisk, Department of Epidemiology and Biostatistics, Medical Centre and the Department of Health Sciences of the Vrije Universteit, Amsterdam.;

250 a| 2nd ed.;

260 a| Cambridge :b| Cambridge University Press,c| 2013.;

300 a| xiv, 321 pages :b| illustrations;

336 a| textb| txt2| rdacontent;

337 a| computerb| c2| rdamedia;

338 a| online resourceb| cr2| rdacarrier;

500 a| First published 2003.;

504 a| Includes bibliographical references and index.;

505 8 a| Machine 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 a| "The emphasis of this book lies more on the application of statistical techniques for longitudinal data analysis and not so much on the mathematical background. In most other books on the topic of longitudinal data analysis, the mathematical background is the major issue, which may not be surprising since (nearly) all the books on this topic have been written by statisticians. Although statisticians fully understand the difficult mathematical material underlying longitudinal data analysis, they often have difficulty in explaining this complex material in a way that is understandable for the researchers who have to use the technique or interpret the results. Therefore, this book is not written by a statistician, but by an epidemiologist. In fact, an epidemiologist is not primarily interested in the basic (difficult) mathematical background of the statistical methods, but in finding the answer to a specific research question; the epidemiologist wants to know how to apply a statistical technique and how to interpret the results. Owing to their different basic interests and different level of thinking, communication problems between statisticians and epidemiologists are quite common. This, in addition to the growing interest in longitudinal studies, initiated the writing of this book: a book on longitudinal data analysis, which is especially suitable for the "non-statistical" researcher (e.g. the epidemiologist). The aim of this book is to provide a practical guide on how to handle epidemiological data from longitudinal studies"--c| Provided by publisher.;

533 a| Electronic reproduction. Ann Arbor, MI : ProQuest, 2015. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries.;

650 0 a| Epidemiologyx| Researchx| Statistical methods.=| ^A280049;

650 0 a| Epidemiologyv| Longitudinal studies.=| ^A687;

650 0 a| Epidemiologyx| Statistical methods.=| ^A305002;

655 4 a| Electronic books.;

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856 40 u| https://ebookcentral.proquest.com/lib/eastcarolina/detail.action?docID=1182964z| Click to View;

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Applied longitudinal data analysis for epidemiology : a practical guide / Jos W.R. Twisk, Department of Epidemiology and Biostatistics, Medical Centre and the Department of Health Sciences of the Vrije Universteit, Amsterdam.

Author/creator	Twisk, Jos W. R., 1962-
Other author	ProQuest (Firm)
Format	Electronic
Edition	2nd ed.
Publication Info	Cambridge : Cambridge University Press, 2013.
Description	xiv, 321 pages : illustrations
Supplemental Content	Click to View
Subjects	Epidemiology--Research. --Statistical methods. Epidemiology--Longitudinal studies. Epidemiology--Statistical methods.

Contents	Machine 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.
Abstract	"The emphasis of this book lies more on the application of statistical techniques for longitudinal data analysis and not so much on the mathematical background. In most other books on the topic of longitudinal data analysis, the mathematical background is the major issue, which may not be surprising since (nearly) all the books on this topic have been written by statisticians. Although statisticians fully understand the difficult mathematical material underlying longitudinal data analysis, they often have difficulty in explaining this complex material in a way that is understandable for the researchers who have to use the technique or interpret the results. Therefore, this book is not written by a statistician, but by an epidemiologist. In fact, an epidemiologist is not primarily interested in the basic (difficult) mathematical background of the statistical methods, but in finding the answer to a specific research question; the epidemiologist wants to know how to apply a statistical technique and how to interpret the results. Owing to their different basic interests and different level of thinking, communication problems between statisticians and epidemiologists are quite common. This, in addition to the growing interest in longitudinal studies, initiated the writing of this book: a book on longitudinal data analysis, which is especially suitable for the "non-statistical" researcher (e.g. the epidemiologist). The aim of this book is to provide a practical guide on how to handle epidemiological data from longitudinal studies"-- Provided by publisher.
General note	First published 2003.
Bibliography note	Includes bibliographical references and index.
Reproduction note	Electronic reproduction. Ann Arbor, MI : ProQuest, 2015. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries.
Genre/form	Electronic books.
LCCN	2012050470

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Applied longitudinal data analysis for epidemiology : a practical guide / Jos W.R. Twisk, Department of Epidemiology and Biostatistics, Medical Centre and the Department of Health Sciences of the Vrije Universteit, Amsterdam.

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