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Linear Probability, Logit, and Probit Models (Quantitative Applications in the Social Sciences)
Ordinary regression analysis is not appropriate for investigating dichotomous or otherwise "limited" dependent variables, but this volume examines three techniques -- linear probability, probit, and logit models -- which are well-suited for such data. It reviews the linear probability model and discusses alternative specifications of non-linear models. Using detailed examples, Aldrich and Nelson point out the differences among linear, logit, and probit models, and explain the assumptions associated with each.
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Have a copy in your library.
By A Customer - April 3, 2001I think that it is a really good monograph about the logit and the probit models. It is very accessible at the appropriate level. I made a great deal use of it. Although it has a introductory review section about the linear regression model, having a good understanding of it, and also of statistics, is necessary in order to understand the rest of the book well.
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By Blue Tyson "- Research Finished" - September 2, 2007A short mathematical tech detailing mathematical techniques that can be used when ordinary regression analysis is not appropriate, valid, or will just not work. The examples given are generally looking at a social science point of view, but the explanation and description is clear and is easily followed for application in other areas.
Accessible Intermediate Text on Linear and GLM Probability Models
By William B. Dwinnell IV - February 17, 2011This is a short book on modeling probabilities using linear and generalized linear models. It walks the conceptual path from least-squares linear regression, through the linear probability model, to logistic and probit regression. This book is not for the statistical novice: A working knowledge of linear models will be necessary to take advantage of this text (knowing something about classification models like logistic regression or discriminant analysis would help, too). The great contribution of this book is that it ties these modeling methods together and answers a number of "why?" questions that anyone with an imagination would ask, after using linear classification models.
Covered include: linear probability model (Goldberger's procedure), basic generalized linear models (notably logistic and probit regressions, though alternative transfer functions are touched upon), both dichotomous and polytomous models and important practical issues.
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Quantile Regression (Quantitative Applications in the Social Sciences) (v. 149)
$12.09 - $18.00Quantile Regression, the first book of Hao and Naiman's two-book series, establishes the seldom recognized link between inequality studies and quantile regression models. Though ...
Interaction Effects in Factorial Analysis of Variance (Quantitative Applications in the Social Sciences)…
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Causal Analysis with Panel Data (Quantitative Applications in the Social Sciences)
$1.00 - $18.00Panel data — information gathered from the same individuals or units at several different points in time — are commonly used in the social sciences to test theories of individual and ...
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$5.00 - $18.53Clustering and tree models are being widely used in the social and biological sciences to analyze similarity relations. This volume describes how matrices of similarities or associations among ...
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$4.46 - $44.50The potentially lively intellectual environment surrounding diffusion models has been restricted by the language and notation employed in different fields. It's a topic which begs for a sound ...
Modern Methods for Robust Regression (Quantitative Applications in the Social Sciences)
$1.00 - $18.95Modern Methods for Robust Regression offers a brief but in-depth treatment of various methods for detecting and properly handling influential cases in regression analysis. This volume, ...
Logit Modeling: Practical Applications (Quantitative Applications in the Social Sciences)
$3.35 - $19.00Logit Modeling represents a breakthrough for researchers because it offers ways for more efficient estimation of models with multiple categorical variables, particularly whenever the ...
Understanding Significance Testing (Quantitative Applications in the Social Sciences)
$11.96 - $18.53Significance testing - a core technique in statistics for hypothesis testing - is introduced in this volume. Mohr first reviews what is meant by sampling and probability distributions and then ...
Multilevel Modeling (Quantitative Applications in the Social Sciences)
$12.89 - $18.00Taking a practical, hands-on approach to multilevel modeling, this book provides readers with an accessible and concise introduction to HLM and how to use the technique to build models for ...
Interaction Effects in Multiple Regression (Quantitative Applications in the Social Sciences)
$14.21 - $18.00Interaction Effects in Multiple Regression has provided students and researchers with a readable and practical introduction to conducting analyses of interaction effects in the ...
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