parmest and extensions
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.
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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.
- Roger Newson & The ALSPAC Study Team, 2003.
"Multiple-test procedures and smile plots,"
StataCorp LP, vol. 3(2), pages 109-132, June.
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