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GLST: Stata module for trend estimation of summarized dose-response data

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Nicola Orsini () (Karolinska Institutet)
Rino Bellocco () (Karolinska Institutet)
Sander Greenland () (UCLA)

Additional information is available for the following registered author(s):

Abstract

glst estimates trend across different exposure levels for either single or multiple summarized case-control, incidence-rate, and cumulative incidence data. This approach is based on constructing an approximate covariance estimate for the log relative risks and estimating a corrected trend using generalized least-squares. For trend analysis of multiple studies (meta-analysis), glst can estimates fixed and random-effects meta-regression models.

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File URL: http://fmwww.bc.edu/repec/bocode/g/glst.ado
File Format: text/plain
File Function: program code
Download Restriction: no
File URL: http://fmwww.bc.edu/repec/bocode/g/glst.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 S452001.

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 9
Date of creation: 08 Jun 2005
Date of revision: 11 May 2009
Handle: RePEc:boc:bocode:s452001

Note: This module may be installed from within Stata by typing "ssc install glst". 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

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

Related research
Keywords: generalized least squares; trend estimation; dose-response data; meta-analysis;

Statistics
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This page was last updated on 2009-12-10.


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