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LINCHECK: Stata module to graphically assess the linearity of a continuous covariate in a regression model

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Alex Gamma () (University of Zurich)
Abstract

lincheck provides a quick-and-dirty check of whether a continuous covariate in a general linearized model (GLM) is linear in the link function. lincheck makes a new categorical variable that breaks the continuous covariate into quartiles, then re-estimates the GLM using dummy variables for the quartiles, and finally provides a graph of estimated coefficients plotted against the midpoints of the quartiles. A linear graph supports the assumption of linearity of the continuous covariate. lincheck works with most GLM commands such as regress, logit/logistic, probit, poisson, stcox etc. and their svy-versions.

Download Info
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File URL: http://fmwww.bc.edu/repec/bocode/l/lincheck.ado
File Format: text/plain
File Function: program code
Download Restriction: no
File URL: http://fmwww.bc.edu/repec/bocode/l/lincheck.hlp
File Format: text/plain
File Function: help file
Download Restriction: no

Publisher Info
Software component provided by Boston College Department of Economics in its series Statistical Software Components with number S449401.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
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Programming language: Stata
Requires: Stata version 8
Date of creation: 28 Feb 2005
Date of revision:
Handle: RePEc:boc:bocode:s449401

Note: This module may be installed from within Stata by typing "ssc install lincheck". Windows users should not attempt to download these files with a web browser.
Contact details of provider:
Postal: Boston College, 140 Commonwealth Avenue, Chestnut Hill MA 02467 USA
Phone: 617-552-3670
Fax: +1-617-552-2308
Email:
Web page: http://fmwww.bc.edu/EC/
More information through EDIRC

Order Information:
Web: http://repec.org/docs/ssc.php

For technical questions regarding this item, or to correct its listing, contact: (Christopher F Baum).

Related research
Keywords: linearity; regression; graphics;

Statistics
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This page was last updated on 2009-12-22.


This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.