sidbp: Data of sitting distolic blood pressure (SiDBP)

In bifactorial: Inferences for bi- and trifactorial trial designs

Description

These data have been simulated with respect to the descriptive statistics given in the bifactorial hypertension clinical trial reported by Hung (2000). Various distributional properties have been realized for normal and skewed cases with equal variances as well as with linearly increasing variances. The latter means that the coefficient of variation is held constant over the treatment groups. The group defining variable is named cb in the data set. It has got the levels (0,0), (1,0), ..., (2,3) according to the respective dose combinations. The data vectors with the different distributional properties are ynrmhom, ynrmhet, yloghom and yloghet.

Format

A data frame with 738 observations on the following 5 variables.

cb

a factor with levels (0,0), (0,1), ..., (2,3)

ynrmhom

A vector of normal and homoscedastic data.

ynrmhet

A vector of normal and heteroscedastic data.

yloghom

A vector of lognormal and homoscedastic data.

yloghet

A vector of lognormal and heteroscedastic data.

References

Hung HMJ (2000): Evaluation of a combination drug with multiple doses in unbalanced factorial design clinical trials. Statistics in Medicine 19, pp. 2079-2087

Examples

data(sidbp)

bifactorial documentation built on May 29, 2017, 9:34 a.m.