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Vernon Gayle, Paul Lambert, Jessica Nina Lester - Quantitative Longitudinal Data Analysis, Inbunden

Inbunden, Engelska, 2020

Quantitative Longitudinal Data Analysis

Research Methods

Av Vernon Gayle, Paul Lambert, Jessica Nina Lester

Del i serien Bloomsbury Research Methods

917 kr

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Beskrivning
First published Open Access under a Creative Commons license as What is Quantitative Longitudinal Data Analysis?, this title is now also available as part of the Bloomsbury Research Methods series.Across the social sciences, there is widespread agreement that quantitative longitudinal research designs offer analysts powerful scientific data resources. But, to date, many texts on analysing longitudinal social analysis surveys have been written from a statistical, rather than a social science data analysis perspective and they lack adequate coverage of common practical challenges associated with social science data analyses.This book provides a practical and up-to-date introduction to influential approaches to quantitative longitudinal data analysis in the social sciences. The book introduces definitions and terms, explains the relative attractions of such a longitudinal design, and offers an introduction to the main techniques of analysis, explaining their requirements, statistical properties and their substantive contribution.
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Vernon Gayle is Professor of Sociology and Social Statistics at the University of Edinburgh, UK.Paul Lambert is Professor of Sociology at the University of Stirling, UK.

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An impressive text for anyone wishing to understand the value of longitudinal data for social science research questions and the analytical techniques and practical approaches required to make effective use of such data. The clear enthusiasm and expertise of the authors for the subject shines through the text, helping the reader navigate the complexities of different kinds of longitudinal data, possible research questions and techniques with ease. It is really clearly written in a very engaging manner with examples and code making it suitable for students and researchers new to longitudinal research as well more experienced analysts.

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