One central and enduring image of the social science researcher is of an individual who commits a great deal of time to collecting original, primary data from a field of enquiry. This approach is often underpinned by a sincerely held belief that key research questions can only be explored by the collection of ever new, and ever greater amounts of data, or that already existing data are insufficient for researchers to test their ideas. Yet such an approach to social science research can be problematic not least because the collection of primary data can be an expensive, time-consuming, and even wasteful approach to social enquiry.

Secondary analysis can serve many purposes, as well as being a valid approach in its own right. However, despite its widespread application, secondary analysis is often undervalued or perceived to be the preserve of only those interested in the re-use of large-scale survey data.

Highlighting both the theory and practice of secondary analysis and the use of secondary sources, this collection considers the nature of secondary analysis as a research tool; reflects on the definitional debates surrounding terms such as secondary analysis, data re-use and restudies; illustrates how secondary analysis is used in social science research; and finally reviews the practical, methodological and ethical aspects of secondary analysis.

Volume 1: Using Secondary Sources and Secondary Analysis provides an overview of the theoretical underpinnings of secondary analysis in social research.

Volume 2: Quantitative Approaches to Secondary Analysis covers the broad range of approaches adopted in quantitative secondary analysis research designs.

Volume 3: Qualitative Data and Research in Secondary Analysis focuses on qualitative research methods that offer the social researcher the opportunity to examine additional themes or explore new concepts and ideas in existing qualitative materials.

Volume 4: Ethical, Methodological and Practical Issues in Secondary Analysis critically evaluates the rise of social data archives and their role in current and future research and reflects upon the ethical dilemmas and pitfalls of using the data collected by others for new research.

Determining the Relative Importance of Predictors in Logistic Regression: An Extension of Relative Weight Analysis

Determining the Relative Importance of Predictors in Logistic Regression: An Extension of Relative Weight Analysis

Determining the Relative Importance of Predictors in Logistic Regression: An Extension of Relative Weight AnalysisScottTonidandelDavidson College, Department of Psychology, sctonidandel@davidson.eduJames M.LeBretonPurdue University, Department of Psychological Sciences13 ppSAGE Publications, Inc.
2455 Teller RoadThousand OaksCalifornia91320United States of America
October 2010134767767781

Contact SAGE Publications at http://www.sagepub.com

10.1177/1094428109341993

Encoding from PDF of original work

‘Determining the Relative Importance of Predictors in Logistic Regression: An Extension of Relative Weight Analysis’,ScottTonidandelJames M.LeBretonOrganizational Research Methods,13(4)(2010):767–781.Published by SAGE Publications, Inc. Reprinted with permission.

Techniques such as dominance analysis and relative weight analysis have been proposed recently to evaluate more accurately predictor ...

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