Berk has incisively identified the various strains of regression abuse
and suggests practical steps for researchers who desire to do good
social science while avoiding such errors." --Peter H. Rossi,
University of Massachusetts, Amherst "I have been waiting for a book
like this for some time. Practitioners, especially those doing applied
work, will have much to gain from Berk′s volume, regardless of their
level of statistical sophistication. Graduate students in sociology,
education, public policy, and any number of similar fields should also
use it. It will also be a useful foil for conventional texts for the
teaching of the regression model. I plan to use it for my students as
a text, and hope others will do the same." --Herbert Smith, Professor
of Demography & Sociology, University of Pennsylvania Regression is
often applied to questions for which it is ill equipped to answer. As
a formal matter, conventional regression analysis does nothing more
than produce from a data set a collection of conditional means and
conditional variances. The problem, though, is that researchers
typically want more: they want tests, confidence intervals and the
ability to make causal claims. However, these capabilities require
information external to that data themselves, and too often that
information makes implausible demands on how nature is supposed to
function. Convenience samples are treated as if they are random
samples. Causal status is given to predictors that cannot be
manipulated. Disturbance terms are assumed to behave not as nature
might produce them, but as required by the model. Regression Analysis:
A Constructive Critique identifies a wide variety of problems with
regression analysis as it is commonly used and then provides a number
of ways in which practice could be improved. Regression is most useful
for data reduction, leading to relatively simple but rich and precise
descriptions of patterns in a data set. The emphasis on description
provides readers with an insightful rethinking from the ground up of
what regression analysis can do, so that readers can better match
regression analysis with useful empirical questions and improved
policy-related research. "An interesting and lively text, rich in
practical wisdom, written for people who do empirical work in the
social sciences and their graduate students." --David A. Freedman,
Professor of Statistics, University of California, Berkeley
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Produktdetaljer
ISBN
9781452244860
Publisert
2013
Utgave
1. utgave
Utgiver
Vendor
SAGE Publications, Inc
Språk
Product language
Engelsk
Format
Product format
Digital bok
Forfatter