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st: New version of -parmest- on SSC

From   "Newson, Roger B" <[email protected]>
To   statalist <[email protected]>
Subject   st: New version of -parmest- on SSC
Date   Sun, 6 Sep 2009 16:49:54 +0100

Thanks to Kit Baum, a new version of -parmest- is now available for download from SSC. In Stata, use the -ssc- command to do this, or -adoupdate- if you already have an earlier version of -parmest-.

The -parmest- package is described as below on my website. The new version is updated to work smoothly with the new Stata 11 -mi estimate- command for multiple imputation, or with any other commands that may be developed in future which use parameter-specific degrees of freedom and/or save multiple estimates vectors, variance matrices and degrees-of-freedom vectors. I have added 3 new options -bmatrix()-, -vmatrix()- and -dfmatrix()-, all of which are given as matrix expressions, identifying the estimates vector, the variance matrix, and the degrees-of-freedom vector, respectively, to be used by -parmest-. These options have sensible defaults, such as -bmatrix(e(b))- and -vmatrix(e(V))- in the case of most estimation commands. However, if the user has just executed a multiple imputation using -mi impute-, as in

use, clear
mi estimate (ratio: _b[age]/_b[sqft]): regress price tax sqft age nfeatures ne custom corner

then the user can type

parmest, list(,) saving(myorig1.dta, replace)

to list confidence intervals and P-values for the original parameters and save them in the file -myorig1.dta-, and can then type

parmest, list(,) bmatrix(e(b_Q_mi)) vmatrix(e(V_Q_mi)) dfmatrix(e(df_Q_mi)) saving(nytran1.dta, replace)

to list the confidence interval for the transformed parameter -ratio- and save it in the file -mytran1.dta-.

Best wishes


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
Tel: +44 (0)20 7352 8121 ext 3381
Fax: +44 (0)20 7351 8322
Email: [email protected] 
Web page:
Departmental Web page:

Opinions expressed are those of the author, not of the institution.

package parmest from

      parmest: Create datasets with 1 observation per estimated parameter

      The parmest package has 4 modules: parmest, parmby, parmcip and metaparm.
      parmest creates an output dataset, with 1 observation per parameter of the
      most recent estimation results, and variables corresponding to parameter names,
      estimates, standard errors, z- or t-test statistics, P-values, confidence
      limits and other parameter attributes. parmby is a quasi-byable extension to
      parmest, which calls an estimation command, and creates a new dataset, with 1
      observation per parameter if the by() option is unspecified, or 1 observation
      per parameter per by-group if the by() option is specified. parmcip inputs
      variables containing estimates, standard errors and (optionally) degrees of
      freedom, and computes new variables containing confidence intervals and
      P-values. metaparm inputs a parmest-type dataset with 1 observation for each
      of a set of independently-estimated parameters, and outputs a dataset with
      1 observation for each of a set of linear combinations of these parameters,
      with confidence intervals and P-values, as for a meta-analysis. The output
      datasets created by parmest, parmby or metaparm  may be listed to the Stata
      log and/or saved to a file and/or retained in memory (overwriting any
      pre-existing dataset). The confidence intervals, P-values and other parameter
      attributes in the dataset may be listed and/or plotted and/or tabulated.
      Author: Roger Newson
      Distribution-Date: 04september2009
      Stata-Version: 11

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