What is Quantitative Longitudinal Data Analysis?

✍ Scribed by Vernon Gayle; Paul Lambert

• Publisher: Bloomsbury Academic
• Year: 2018
• Tongue: English
• Leaves: 169
• Category: Library

✦ Synopsis

Across the social sciences, there is widespread agreement that quantitative longitudinal research designs offer analysts powerful scientific data resources. But, to date, most 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 provides an accessible introduction to the main techniques of analysis, explaining their requirements, statistical properties and their substantive contribution
The book is designed for postgraduates and researchers across the social sciences considering the use of quantitative longitudinal data resources in their research. It will also be an excellent text for undergraduate and postgraduate courses on advanced quantitative methods.

✦ Table of Contents

Title Page
Copyright Page
Contents
List of figures
List of tables
Preface
Series editor’s foreword
Acknowledgements
Chapter 1: Introduction to quantitative longitudinal data
Introduction 
Cross-sectional social surveys 
Longitudinal social surveys with repeated contacts
Modes of survey data collection 
The Research value of repeated contacts quantitative longitudinal data
Conclusions 
Chapter 2: Quantitative longitudinal datasets
Large-scale panel studies 
The British Household Panel Survey 
UK Household Longitudinal Study – Understanding society
Cohort studies 
The major British cohort studies 
Other British birth cohort studies 
Other longitudinal studies 
Cross-national and comparative longitudinal studies
Conclusions 
Chapter 3: Temporal analysis with cross-sectional data
Introduction 
Comparing survey measures 
An example of analysing pooled cross-sectional surveys
Cross-national comparative research using repeated cross-sectional surveys
Conclusions 
Chapter 4: The analysis of duration data
Introduction 
Measuring durations 
Duration models 
Parametric duration models 
Competing risk models 
Discrete-time models 
Conclusions 
Chapter 5: The analysis of repeated contacts data
Introduction 
Approaches to analysing panel data: Part 1
Approaches to analysing panel data: Part 2
Comparing different panel models: Example 1
Comparing different panel models: Example 2
Comparing fixed effects panel models and random effects panel models
Panel models for binary outcomes 
Panel models with other outcomes 
Dynamic panel models 
Estimating random effects models in Stata
Conclusions 
Chapter 6: Adopting the long view: A review of analytical methods
The main message 
Using existing datasets 
Statistical models for quantitative  longitudinal analyses
Further methodological issues 
Speculation on the future of longitudinal  social science datasets and other emerging resources
Conclusions 
Chapter 7: Getting started
The workflow 
Data enabling 
Using Stata 
Longitudinal data structures in Stata 
Last words 
Data citations 
Bibliography
Index