distdichogen {distdichoR}

normal, skew-normal or gamma distributed data

Description

distdichogen first returns the results of a two-group unpaired t-test. Followed by 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. distdicho_gen takes normal (dist = 'normal'), skew normal (dist = 'sk_normal') and gamma (dist = 'gamma') distributed data. The data can either be given as two variables, which provide the outcome in each group or specified as a formula of the form lhs ~ rhs where lhs is a numeric variable giving the data values and rhs a factor with two levels giving the corresponding exposed and unexposed groups. In all cases, it is assumed that there are only two groups.

Usage

distdichogen(x, ...)

## Default S3 method:
distdichogen(x, y, cp = 0, tail = c("lower", "upper"),
  conf.level = 0.95, dist = c("normal", "sk_normal", "gamma"),
  bootci = FALSE, nrep = 2000, ...)

## S3 method for class 'formula'
distdichogen(formula, data, exposed, ...)

Arguments

x

A numeric vector of data values.

...

Further arguments to be passed to or from methods.

y

A numeric vector of data values.

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 data. Must be either 'normal' (default), 'sk_normal or 'gamma'.

bootci

A logical variable indicating whether bootstrap bias-corrected confidence intervals are calculated instead of distributional ones.

nrep

A numeric value, specifies the number of bootstrap replications (nrep must be higher than the number of observations).

formula

A formula of the form lhs ~ rhs where lhs is a numeric variable giving the data values and rhs a factor with two levels giving the corresponding exposed and unexposed groups.

data

An optional matrix or data frame containing the variables in the formula. By default, the variables are taken from environment(formula).

exposed

A character string specifying the grouping value of the exposed group.

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 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.

ttest

A list containing the results of a t-test.

References

Peacock J.L., Sauzet O., Ewings S.M., Kerry S.M. Dichotomising continuous data while retaining statistical power using a distributional approach. Statist. Med; 2012; 26:3089-3103. Sauzet, O., Peacock, J. L. Estimating dichotomised outcomes in two groups with unequal variances: a distributional approach. Statist. Med; 2014 33 4547-4559 ;DOI: 10.1002/sim.6255. Sauzet, O., Ofuya, M., Peacock, J. L. Dichotomisation using a distributional approach when the outcome is skewed BMC Medical Research Methodology 2015, 15:40; doi:10.1186/s12874-015-0028-8. 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, distdichoigen, regdistdicho

Examples

## Proportions of low birth weight babies among smoking and non-smoking mothers
## (data from Peacock et al. 1995). Returns distributional estimates, standard 
## errors and distributional confidence intervals for differences in proportions,
## RR and OR of babies having a birth weight under 2500g (low birth weight)
## for group smoker (mother smokes) over the odds of LBW in group non-smoker 
## (mother doesn't smoke)
# Formula interface
distdichogen(birthwt ~ smoke, cp = 2500, data = bwsmoke, exposed = 'smoker',
             dist = 'sk_normal')
# Data stored in two vectors
bw_smoker <- bwsmoke$birthwt[bwsmoke$smoke == 'smoker']
bw_nonsmoker <- bwsmoke$birthwt[bwsmoke$smoke == 'non-smoker']
distdichogen(x = bw_smoker, y = bw_nonsmoker, 
              cp = 2500, tail = 'lower', dist = 'sk_normal')


## Body Mass Index (BMI) and parity. Returns distributional estimates, standard
## errors and distributional confidence intervals for difference in proportions,
## RR and OR of obese mothers (BMI of >30kg/m^2) for group_par=1 (multiparity) 
## over the odds of obesity in group_par=0 (primiparity)
distdichogen(bmi ~ group_par, cp = 30, data = bmi, exposed = '1',
             tail = 'upper', dist = 'sk_normal')