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parmest and extensions

Listed author(s):
  • Roger Newson


    (National Heart and Lung Institute, Imperial College London)

The parmest package creates output datasets (or results sets) with one observation for each of a set of estimated parameters, and data on the parameter estimates, standard errors, degrees of freedom, t or z statistics, p-values, confidence limits, and other parameter attributes specified by the user. It is especially useful when parameter estimates are "mass-produced", as in a genome scan. Versions of the package have existed on SSC since 1998, when it contained the single command parmest. However, the package has since been extended with additional commands. The metaparm command allows the user to mass-produce confidence intervals for linear combinations of uncorrelated parameters. Examples include confidence intervals for a weighted arithmetic or geometric mean parameter in a meta-analysis, or for differences or ratios between parameters, or for interactions, defined as differences (or ratios) between differences. The parmcip command is a lower-level utility, inputting variables containing estimates, standard errors, and degrees of freedom, and outputting variables containing confidence limits and p-values. As an example, we can input genotype frequencies and calculate confidence intervals for geometric mean homozygote/heterozygote ratios for genetic polymorphisms, measuring the size and direction of departures from Hardy-Weinberg equilibrium.

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Paper provided by Stata Users Group in its series United Kingdom Stata Users' Group Meetings 2008 with number 07.

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Date of creation: 11 Sep 2008
Handle: RePEc:boc:usug08:07
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  1. Roger Newson & The ALSPAC Study Team, 2003. "Multiple-test procedures and smile plots," Stata Journal, StataCorp LP, vol. 3(2), pages 109-132, June.
  2. Roger Newson, 2003. "Confidence intervals and p-values for delivery to the end user," Stata Journal, StataCorp LP, vol. 3(3), pages 245-269, September.
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