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This book examines subjective wellbeing in China in terms of life and job satisfaction from a longitudinal perspective during the last decade. Using quantitative methods, the research presented in this volume performed a longitudinal analysis of data collected by the China Family Panel Studies (CFPS) from 2010 to 2018 to study the effects of social and economic transformations on life and job satisfaction among the Chinese population in this period.
Using Mplus software, the authors applied different quantitative methods of longitudinal analysis - such as latent growth models (LGM), latent
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Produktbeschreibung
This book examines subjective wellbeing in China in terms of life and job satisfaction from a longitudinal perspective during the last decade. Using quantitative methods, the research presented in this volume performed a longitudinal analysis of data collected by the China Family Panel Studies (CFPS) from 2010 to 2018 to study the effects of social and economic transformations on life and job satisfaction among the Chinese population in this period.

Using Mplus software, the authors applied different quantitative methods of longitudinal analysis - such as latent growth models (LGM), latent growth mixture model (LGMM), parallel analysis, cross-lagged models (CL), latent change score (LCS), and multilevel longitudinal models (MLM) - to explore the trajectory of three variables on the CFPS data between 2010 and 2018: life satisfaction, job satisfaction and the interplay between job and life satisfaction. Theresults reveal a process of growing inequalities between life and job satisfaction among the Chinese population over time.

Life and Job Satisfaction in China: Exploring Longitudinal Analysis with Mplus will be of interest to sociologists, statisticians and applied researchers interested in applying quantitative methods to develop longitudinal studies of quality of life in China.


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Autorenporträt
Delfino Vargas Chanes is a full professor at the National Autonomous University of Mexico. He earned his Ph.D. in sociology, MS in statistics and MS in sociology from Iowa State University, and his BS in mathematics from the National Autonomous University of Mexico. He has published more than 50 articles and two books. His areas of interest are the study of poverty, inequality, and advanced methods in statistics applied to social sciences, such as structural equation models, multilevel modelling, and machine learning. He belongs to the Mexican National System of Researchers.

Lukasz Czarnecki is a professor at the University of the National Education Commission, Krakow, Poland, and at Instituto Campechano, Mexico. He holds two PhDs in sociology - one from the National Autonomous University of Mexico and another from the University of Strasbourg, France - and a Juris Doctoris title from the Jagiellonian University of Krakow. His areas of interest include the intersections between sociology and subjective well-being with an application of structural equation modelling in the research on inequalities and other quantitative methods, including longitudinal analysis, oriented to apply mixed methods research. He is a member of the Mexican National System of Researchers.