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POSTRRI: Stata module to calculate posterior relative risks

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

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

Abstract

postrri provides an easy way to do Bayesian analyses via inverse-variance (information) weighted averaging of the prior with the frequentist relative risk. It is an immediate command, see help immed.

Download Info
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File URL: http://fmwww.bc.edu/repec/bocode/p/postrri.ado
File Format: text/plain
File Function: program code
Download Restriction: no
File URL: http://fmwww.bc.edu/repec/bocode/p/postrri.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 S456794.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Size:
Programming language: Stata
Requires: Stata version 8.2
Date of creation: 21 Nov 2006
Date of revision:
Handle: RePEc:boc:bocode:s456794

Note: This module may be installed from within Stata by typing "ssc install postrri". 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: Bayesian analysis; inverse-variance (information) weighted average; relative risks;

Statistics
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This page was last updated on 2009-12-9.

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.