regdistdicho {distdichoR}

normal, skew-normal or gamma distributed data (via linear regression)

Description

Provides adjusted distributional estimates for the comparison of proportions for a dichotomised dependent continuous variable derived from a linear regression of the continuous outcome on the grouping variable and other covariates as described in Sauzet et al. 2015.

Usage

regdistdicho(mod, group_var, cp = 0, tail = c("lower", "upper"),
  conf.level = 0.95, dist = c("normal", "sk_normal", "gamma"), alpha = 1)

Arguments

mod

A linear model of the form lm(lhs ~ rhs) where lhs is a numeric variable giving the data values and rhs is the grouping variable and other covariates.

group_var

A character string specifying the name of the grouping variable.

cp

A numeric value specifying the cut point under which the distributional proportions are computed.

tail

A character string specifying the tail of the distribution in which the proportions are computed, must be either 'lower' (default) or 'upper'.

conf.level

Confidence level of the interval.

dist

A character string specifying the distribution of the error variable in the linear regression, must be either 'normal' (default), 'sk_normal or 'gamma'.

alpha

A numeric value specifying further parameter of the skew normal / gamma distribution.

Details

regdistdicho returns the distributional estimates and their standard errors (see Sauzet et al. 2014 and Peacock et al. 2012) for a difference in proportions, risk ratio and odds ratio. It also provides the distributional confidence intervals for the statistics estimated. The estimation is based on the marginal means of a linear regression of the outcome on the grouping variable and other covariates.

Value

A list with class 'distdicho' containing the following components:

data.name

The names of the data.

arguments

A list with the specified arguments.

parameter

The marginal mean, standard error and number of observations for both groups.

prop

The estimated proportions below / above the cut point for both groups.

dist.estimates

The difference in proportions, risk ratio and odds ratio of the groups.

se

The estimated standard error of the difference in proportions, the risk ratio and the odds ratio.

ci

The confidence intervals of the difference in proportions, the risk ratio and the odds ratio.

method

A character string indicating the used method.

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).

See Also

distdicho, distdichoi, distdichogen, distdichoigen

Examples

## Proportions of low birth weight babies among smoking and non-smoking mothers
## (data from Peacock et al. 1995)
mod_smoke <- lm(birthwt ~ smoke + gest, data = bwsmoke)
regdistdicho(mod = mod_smoke, group_var = 'smoke', cp = 2500, tail = 'lower')