skip to content
Regression models for categorical dependent variables using Stata Preview this item
ClosePreview this item
Checking...

Regression models for categorical dependent variables using Stata

Author: J Scott Long; Jeremy Freese
Publisher: College Station, Texas : Stata Press, 2014. ©2014
Edition/Format:   Print book : English : Third editionView all editions and formats
Database:WorldCat
Summary:
After reviewing the linear regression model and introducing maximum likelihood estimation, Long extends the binary logit and probit models, presents multinomial and conditioned logit models and describes models for sample selection bias.
Rating:

(not yet rated) 0 with reviews - Be the first.

Subjects
More like this

 

Find a copy in the library

&AllPage.SpinnerRetrieving; Finding libraries that hold this item...

Details

Document Type: Book
All Authors / Contributors: J Scott Long; Jeremy Freese
ISBN: 9781597181112 1597181110
OCLC Number: 890178695
Description: xxiii, 589 pages : illustrations ; 24 cm
Contents: I. General information. Introduction --
Introduction to Stata --
Estimation, testing, and fit --
Methods of interpretation --
II. Models for specific kinds of outcomes. Models for binary outcomes : estimation, testing, and fit --
Models for binary outcomes : interpretation --
Models for ordinal outcomes --
Models for nominal outcomes --
Models for count outcomes.
Responsibility: J. Scott Long, Departments of Sociology and Statistics, Indiana University, Bloomington, Indiana, Jeremy Freese, Department of Sociology and Institute for Policy Research, Northwestern University, Evanston, Illinois.
More information:

Abstract:

After reviewing the linear regression model and introducing maximum likelihood estimation, Long extends the binary logit and probit models, presents multinomial and conditioned logit models and  Read more...

Reviews

User-contributed reviews
Retrieving GoodReads reviews...
Retrieving DOGObooks reviews...

Tags

Be the first.
Confirm this request

You may have already requested this item. Please select Ok if you would like to proceed with this request anyway.

Linked Data


Primary Entity

<http://www.worldcat.org/oclc/890178695> # Regression models for categorical dependent variables using Stata
    a schema:CreativeWork, schema:Book ;
    library:oclcnum "890178695" ;
    library:placeOfPublication <http://id.loc.gov/vocabulary/countries/txu> ;
    schema:about <http://experiment.worldcat.org/entity/work/data/11709968#Topic/social_sciences_statistical_methods_data_processing> ; # Social sciences--Statistical methods--Data processing
    schema:about <http://experiment.worldcat.org/entity/work/data/11709968#CreativeWork/stata> ; # Stata.
    schema:about <http://experiment.worldcat.org/entity/work/data/11709968#Topic/regression_analysis> ; # Regression analysis
    schema:about <http://dewey.info/class/519.536/e23/> ;
    schema:author <http://experiment.worldcat.org/entity/work/data/11709968#Person/freese_jeremy> ; # Jeremy Freese
    schema:author <http://experiment.worldcat.org/entity/work/data/11709968#Person/long_j_scott> ; # J. Scott Long
    schema:bookEdition "Third edition." ;
    schema:bookFormat bgn:PrintBook ;
    schema:copyrightYear "2014" ;
    schema:datePublished "2014" ;
    schema:description "I. General information. Introduction -- Introduction to Stata -- Estimation, testing, and fit -- Methods of interpretation -- II. Models for specific kinds of outcomes. Models for binary outcomes : estimation, testing, and fit -- Models for binary outcomes : interpretation -- Models for ordinal outcomes -- Models for nominal outcomes -- Models for count outcomes."@en ;
    schema:description ""The goal of Regression Models for Categorical Dependent Variables Using Stata, Third Edition is to make it easier to carry out the computations necessary to fully interpret regression models for categorical outcomes by using Stata's margins command. Because the models are nonlinear, they are more complex to interpret. Most software packages that fit these models do not provide options that make it simple to compute the quantities useful for interpretation. In this book, the authors briefly describe the statistical issues involved in interpretation, and then they show how you can use Stata to perform these computations."--Back cover."@en ;
    schema:description "After reviewing the linear regression model and introducing maximum likelihood estimation, Long extends the binary logit and probit models, presents multinomial and conditioned logit models and describes models for sample selection bias."@en ;
    schema:exampleOfWork <http://worldcat.org/entity/work/id/11709968> ;
    schema:inLanguage "en" ;
    schema:name "Regression models for categorical dependent variables using Stata"@en ;
    schema:productID "890178695" ;
    schema:workExample <http://worldcat.org/isbn/9781597181112> ;
    umbel:isLike <http://bnb.data.bl.uk/id/resource/GBB4B6913> ;
    wdrs:describedby <http://www.worldcat.org/title/-/oclc/890178695> ;
    .


Related Entities

<http://experiment.worldcat.org/entity/work/data/11709968#Person/freese_jeremy> # Jeremy Freese
    a schema:Person ;
    schema:familyName "Freese" ;
    schema:givenName "Jeremy" ;
    schema:name "Jeremy Freese" ;
    .

<http://experiment.worldcat.org/entity/work/data/11709968#Person/long_j_scott> # J. Scott Long
    a schema:Person ;
    schema:familyName "Long" ;
    schema:givenName "J. Scott" ;
    schema:name "J. Scott Long" ;
    .

<http://experiment.worldcat.org/entity/work/data/11709968#Topic/regression_analysis> # Regression analysis
    a schema:Intangible ;
    schema:name "Regression analysis"@en ;
    .

<http://experiment.worldcat.org/entity/work/data/11709968#Topic/social_sciences_statistical_methods_data_processing> # Social sciences--Statistical methods--Data processing
    a schema:Intangible ;
    schema:name "Social sciences--Statistical methods--Data processing"@en ;
    .

<http://worldcat.org/isbn/9781597181112>
    a schema:ProductModel ;
    schema:isbn "1597181110" ;
    schema:isbn "9781597181112" ;
    .


Content-negotiable representations

Close Window

Please sign in to WorldCat 

Don't have an account? You can easily create a free account.