Thanks to Kit Baum, a new package -invcise- is now available for download from SSC. In Stata, use the -ssc- command to do this.
The -invcise- package is described as below on my website. Like with the SSC package -bpmedian- recently announced, it enables the calculation of confidence intervals and P-values for interactions and meta-analysis summaries using rank statistics.
Best wishes
Roger
Roger B Newson BSc MSc DPhil
Lecturer in Medical Statistics
Respiratory Epidemiology and Public Health Group
National Heart and Lung Institute
Imperial College London
Royal Brompton Campus
Room 33, Emmanuel Kaye Building
1B Manresa Road
London SW3 6LR
UNITED KINGDOM
Tel: +44 (0)20 7352 8121 ext 3381
Fax: +44 (0)20 7351 8322
Email: [email protected]
Web page: http://www.imperial.ac.uk/nhli/r.newson/
Departmental Web page:
http://www1.imperial.ac.uk/medicine/about/divisions/nhli/respiration/popgenetics/reph/
Opinions expressed are those of the author, not of the institution.
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package invcise from http://www.imperial.ac.uk/nhli/r.newson/stata10
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TITLE
invcise: Compute standard errors using the inverse confidence interval method
DESCRIPTION/AUTHOR(S)
invcise is intended for use in an output dataset (or resultsset), with
one observation for each of a set of estimated parameters, and
variables containing their confidence limits, and (optionally)
containing the degrees of freedom used to calculate these confidence
limits. Such datasets may be produced using the official Stata
statsby prefix, or by the parmest package, downloadable from SSC.
invcise uses the confidence limits to compute a new variable,
containing standard errors for the parameters, using the inverse
confidence interval method. These standard errors, together with
parameter estimates in another variable in the dataset, may be used to
calculate standard errors and confidence intervals for linear
combinations of these parameters, using the metaparm module of the
parmest package, assuming that the parameters are independently
estimated. The inverse confidence interval method is frequently used
with rank statistics, such as medians, median differences, and median
slopes, to compute confidence intervals for linear combinations of
these rank statistics, particularly differences between differences
("interactions") or weighted means of several differences
("meta-analysis summaries").
Author: Roger Newson
Distribution-Date: 03june2009
Stata-Version: 10
INSTALLATION FILES (click here to install)
invcise.ado
invcise.sthlp
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