000 03205 a2200421 4500
001 1136705473
005 20250317100406.0
008 250312042013GB eng
020 _a9781136705472
037 _bTaylor & Francis
_cGBP 53.99
_fBB
040 _a01
041 _aeng
072 7 _aJMB
_2thema
072 7 _aPBT
_2thema
072 7 _aGPS
_2thema
072 7 _aMBNS
_2thema
072 7 _aJHB
_2thema
072 7 _aJMB
_2bic
072 7 _aPBT
_2bic
072 7 _aGPS
_2bic
072 7 _aMBNS
_2bic
072 7 _aJHB
_2bic
072 7 _aPSY032000
_2bisac
072 7 _aPSY030000
_2bisac
072 7 _aPSY043000
_2bisac
072 7 _aSOC013000
_2bisac
072 7 _aMED090000
_2bisac
072 7 _aPSY000000
_2bisac
072 7 _a300.72
_2bisac
100 1 _aJason Newsom
245 1 0 _aLongitudinal Data Analysis
_bA Practical Guide for Researchers in Aging, Health, and Social Sciences
250 _a1
260 _aOxford
_bRoutledge
_c20130619
300 _a405 p
520 _bThis book provides accessible treatment to state-of-the-art approaches to analyzing longitudinal studies. Comprehensive coverage of the most popular analysis tools allows readers to pick and choose the techniques that best fit their research. The analyses are illustrated with examples from major longitudinal data sets including practical information about their content and design. Illustrations from popular software packages offer tips on how to interpret the results. Each chapter features suggested readings for additional study and a list of articles that further illustrate how to implement the analysis and report the results. Syntax examples for several software packages for each of the chapter examples are provided at www.psypress.com/longitudinal-data-analysis . Although many of the examples address health or social science questions related to aging, readers from other disciplines will find the analyses relevant to their work. In addition to demonstrating statistical analysis of longitudinal data, the book shows how to interpret and analyze the results within the context of the research design. The methods covered in this book are applicable to a range of applied problems including short- to long-term longitudinal studies using a range of sample sizes. The book provides non-technical, practical introductions to the concepts and issues relevant to longitudinal analysis. Topics include use of publicly available data sets, weighting and adjusting for complex sampling designs with longitudinal studies, missing data and attrition, measurement issues related to longitudinal research, the use of ANOVA and regression for average change over time, mediation analysis, growth curve models, basic and advanced structural equation models, and survival analysis. An ideal supplement for graduate level courses on data analysis and/or longitudinal modeling taught in psychology, gerontology, public health, human development, family studies, medicine, sociology, social work, and other behavioral, social, and health sciences, this multidisciplinary book will also appeal to researchers in these fields.
700 1 _aRichard N. Jones
_4B01
700 1 _aScott M. Hofer
_4B01
999 _c1802
_d1802