Leif E. Peterson () (Methodist Hospital Research Institute)
Abstract
When using (unconditional) binary logistic regression modeling, the influence of confounders and nuisance parameters on a specific risk factor or treatment requires a comparison between the unadjusted odds ratio (OR) from a univariate model and the adjusted OR from a multivariate model for the specific factor. The additional covariates used in the multivariate model can consist of variables that are associated with the outcome, variable that are significantly different across groups (e.g., confounders), or nuisance parameters for which the role on the causal pathway are not entirely understood. For a specified unconditional logistic model, the mulogit program appends the multivariate and univariate ORs and 95% CIs into the data set using the data editor, and then constructs graphs showing both the multivariate and univariate results. Users interested in publishing the ORs and CIs can directly cut and paste results from the Stata data editor into other applications, and can paste the resulting graphs into presentation and publication applications. Mulogit was designed to accelerate productivity when both multivariate and univariate OR and CI are needed.
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Publisher Info
Software component provided by Boston College Department of Economics in its series Statistical Software Components with number
S456921.
Size: Programming language: Stata Requires: Stata version 10.0 Date of creation: 02 Apr 2008 Date of revision: Handle: RePEc:boc:bocode:s456921
Note: This module may be installed from within Stata by typing "ssc install mulogit". 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