Sage Secondary Data Analysis


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Archival and Secondary Data


Archival and Secondary Data

Author: Tarani Chandola

language: en

Publisher: SAGE

Release Date: 2022-03-01


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Data archives provide rich and expansive sources of information for researchers. This book highlights the utility of secondary data analyses whilst showing you how to select the right datasets for your study, and in turn get the most out of your research. Topics include: · Generating your research question · Selecting appropriate datasets and variables · Examining univariate, bivariate and multivariate associations · Visualisng your data with tables and graphs Part of The SAGE Quantitative Research Kit, this book boosts students with know-how and confidence, to help them succeed on their quantitative research journey.

Qualitative Secondary Analysis


Qualitative Secondary Analysis

Author: Kahryn Hughes

language: en

Publisher: SAGE

Release Date: 2019-12-02


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A comprehensive guide to carrying out Qualitative Secondary Analysis (QSA) that brings together expert advice and professional insight from leading researchers who have developed innovative theories and methods of QSA. Exploring crucial components of research and analysis—such as where to find resources, how to search within a resource, and working with both paper archives and non-textual data—each chapter offers insightful case studies, links to further reading and applied helpful hints and tips to help effectively apply these innovations to further the reader’s own research. A must read for Social Science students, early career researchers and researchers new to the field of QSA, this text will help readers through every aspect of a research process using QSA, from application to implications.

Secondary Analysis of Survey Data


Secondary Analysis of Survey Data

Author: K. Jill Kiecolt

language: en

Publisher: SAGE

Release Date: 1985


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This volume presents strategies for locating survey data and provides a comprehensive guide to US social science data archives, describing several major data files. Although the data sets are American, the techniques are widely applicable.