Books : Regression with Dummy Variables (Quantitative Applications in the Social Sciences)

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Author name: Melissa A. Hardy

 : Regression with Dummy Variables (Quantitative Applications in the Social Sciences)
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Type of bind: Paperback
Dewey Decimal Number: 300.1519536
EAN num: 9780803951280
ISBN number: 0803951280
Label: Sage Publications, Inc
Manufacturer: Sage Publications, Inc
Quantity: 1
Page Count: 96
Printing Date: February 25, 1993
Publishing house: Sage Publications, Inc
Sale Popularity Level: 108852
Studio: Sage Publications, Inc




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Social scientists are often interested in studying differences in groups, such as gender or race differences in attitudes, buying behaviors, or socioeconomic characteristics. When the researcher seeks to estimate group differences through the use of independent variables that are qualitative (i.e., measured at only the nominal level), dummy variables will allow the researcher to represent information about group membership in quantitative terms without imposing unrealistic measurement assumptions on the categorical variables. Beginning with the simplest model, Hardy probes the use of dummy variable regression in increasingly complex specifications, exploring issues such as: interaction, heteroscedasticity, multiple comparisons and significance testing, the use of effects or contrast coding, testing for curvilinearity, and estimating a piecewise linear regression.





Customer Reviews
User popularity level:  out of 5 stars

Rated by buyers 5 out of 5 stars - Clearly written, understandable, and enormously helpful
Like most of the books in the Sage Quantitative Applications in the Social Sciences, this is clearly written and understandable. This is one of those rare statistics texts that is readable and useful. If you need to understand or use dummy variables in regression, this book will save you enormous amounts of time and frustration. Strongly recommended.



Rated by buyers 5 out of 5 stars - for any grad student facing prelims
This book saved my life! It provided clear explanations and great examples of how to use and interpret regressions with dummy variables. I don't know how I would have passed without it. An extra bonus for people interested in strat--the examples deal with inequality.



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