*! version 8 07Oct2015

Title

reg_distdicho-- Provides adjusted distributional estimates for
the comparison of proportions for a dichotomised dependent continuous
variable derived from a linear (mixed) regression model on the continuous
outcome as described in Sauzet et al 2015.

Syntax

Distributional estimates based on marginal means obtained from a linear (mixed) model.

reg_distdicho
varname
[, options] cp(#)

options

Main
cp(#) value of the cut-point under or above which to compute proportions

tail(string) provides the tail of the distribution in which the proportions are computed

dist(string) provides the distribution to be used

where varname is a factor variable (exposure)that
appears in the current estimation results. See examples belows.

Description

reg_distdicho provides the distributional estimates and their standard errors
(see Sauzet et al 2014 and Peacock et al 2012) for a difference in
proportion, risk ratio and odds ratio comparing the different levels of exposure to the reference level with
95% distributional confidence interval for the statistics. The estimation is based on the marginal means of
the linear (mixed) regression saved results.

Options

Main

cp specifies the cutpoint under or above which the distributional proportions in group1
and group2 are computed.
cp requires a real number. When no value is given a cutpoint of 0 is used.

tail(string) provides the tail of the distribution in which the proportions are to
be computed. The default is the lower tail, upper will provide estimates
in the upper tail.

dist(string) The default is that the residuals are assumed normally distributed. If there remain a perturbation to the normal distribution, the skew-normal method can be used with the option dist(sk)

Remarks

regdistdicho uses the current saved results of a linear (mixed) model (e.g. of regress,
mixed or xtreg).

Confidence intervals are returned using the current level in the system. This level can be modified
using the command set level.

Examples

setup

. use bwsmoke

Proportions of low birthweight babies among smoking and non-smoking mothers (Data from Peacock et al 1995)

Model fitted by regress

. regress birthwt i.smoke gest

. reg_distdicho smoke, tail(lower) cp(2500)

setup

. use http://www.stata-press.com/data/mlmus2/smoking

Model fitted by mixed

. mixed birwt i.smoke mage year, ||momid:

. reg_distdicho smoke, tail(lower) cp(2500)

Model fitted by xtreg

. xtreg birwt i.smoke mage year i.black i.married,i(momid)

. reg_distdicho smoke, tail(lower) cp(2500)

Stored results

reg_distdicho stores the following in r() if thre are only two levels of risk:

Scalars

r(prop1) distributional proportion estimate for group1

r(prop2) distributional proportion estimate for group2

r(propdiff) distributional estimate for the difference in
proportions between group1 and group2

r(distrr) distributional estimate for risk ratio between
group1 and group2

r(distor) distributional estimate for odds ratio between
group1 and group2

r(sediff) standard error for the distributional estimate o
f the difference in proportion

r(serr) standard error for the distributional estimate of
the risk ratio

r(seor) standard error for the distributional estimate of
the odds ratio

r(ciinf) difference in proportions: lower limit of the
confidence interval

r(cisup) difference in proportions: upper limit of the
confidence interval

r(ciinfrr) risk ratio: lower limit of the confidence interval

r(cisuprr) risk ratio: upper limit of the confidence interval

r(ciinfor) odss ratio: lower limit of the confidence interval

r(cisupor) odds ratio: upper limit of the confidence interval

References

Peacock J.L., Sauzet O., Ewings S.M., Kerry S.M. Dichotomising continuous
data while retaining statistical power using a distributional approach.
2012 Statist. Med; 26:3089-3103.

Sauzet, O., Peacock, J. L. Estimating dichotomised outcomes in two groups
with unequal variances: a distributional approach. 2014 Statist. Med;
33 4547-4559 ;DOI: 10.1002/sim.6255.

Sauzet, O., Brekenkamp, J., Brenne, S. , Borde, T., David, M., Razum, O.,
Peacock, J.L. 2015. A distributional approach to obtain adjusted differences
in population at risk with a comparison with other regressions methods using
perinatal data. In preparation.

Peacock, J.L., Bland, J.M., Anderson, H.R.: Preterm delivery: effects of
socioeconomic factors, psychological stress, smoking, alcohol, and caffeine.
BMJ 311(7004), 531{535 (1995).

Authors

Odile Sauzet, Universität Bielefeld , odile.sauzet@uni-bielefeld.de

Maren Kleine , Universität Bielefeld

07.10.2015