This volume covers the commonly ignored topic of heteroskedasticity (unequal error variances) in regression analyses and provides a practical guide for how to proceed in terms of testing and correction. Emphasizing how to apply diagnostic tests and corrections for heteroskedasticity in actual data analyses, the book offers three approaches for dealing with heteroskedasticity: variance-stabilizing transformations of the dependent variable;calculating robust standard errors, or heteroskedasticity-consistent standard errors; andgeneralized least squares estimation coefficients and standard errors. The detection and correction of heteroskedasticity is illustrated with three examples that vary in terms of sample size and the types of units analyzed (individuals, households, U.S. states). Intended as a supplementary text for graduate-level courses and a primer for quantitative researchers, the book fills the gap between the limited coverage of heteroskedasticity provided in applied regression textbooks and the more theoretical statistical treatment in advanced econometrics textbooks.
Robert L. (Temple University, USA) Kaufman
Heteroskedasticity in Regression : Detection and Correction [PDF ebook]
Detection and Correction
Heteroskedasticity in Regression : Detection and Correction [PDF ebook]
Detection and Correction
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لغة الإنجليزية ● شكل PDF ● صفحات 112 ● ISBN 9781483303826 ● الناشر SAGE Publications US ● نشرت 2013 ● للتحميل 6 مرات ● دقة EUR ● هوية شخصية 5360076 ● حماية النسخ Adobe DRM
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