Panel data - information gathered from the same individuals or units at several different points in time - are commonly used in the social sciences to test theories of individual and social change. This book highlights the developments in this technique in a range of disciplines and analytic traditi
Analyzing Panel Data (Quantitative Applications in the Social Sciences)
โ Scribed by Gregory B. Markus
- Publisher
- Sage Publications, Inc
- Year
- 1979
- Tongue
- English
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
An introduction to a variety of techniques that may be used in the analysis of data from a panel study -- information obtained from a large number of entities at two or more points in time. The focus of this volume is on analysis rather than problems of sampling or design, and its emphasis is on application rather than theory.
๐ SIMILAR VOLUMES
This book examines ways to analyze complex surveys, and focuses on the problems of weights and design effects. This new edition incorporates recent practice of analyzing complex survey data, introduces the new analytic approach for categorical data analysis (logistic regression), reviews new softwar
Focusing on an analysis of models and data that arise from repeated observations of a cross-section of individuals, households or firms, this book also covers important applications within business, economics, education, political science and other social science disciplines. The author introduces
By examining some of the basic scaling questions, such as the importance of measurement levels, the kinds of variables needed for Likert or Guttman scales and when to use multidimensional scaling versus factor analysis, Jacoby introduces readers to the most appropriate scaling strategies for differe
If you need hints on how to collect, describe, compare and analyze data, you will find them in this handy guide. The author addresses specification elaboration, and sampling of the "domain" or what is to be sorted. There is also help on setting the criterion, the pre-test, administration, and record
Emphasizing the parallels between linear and logistic regression, Scott Menard explores logistic regression analysis and demonstrates its usefulness in analyzing dichotomous, polytomous nominal, and polytomous ordinal dependent variables. The book is aimed at readers with a background in bivariate a