AssignCovariatesNormBin: Create indepedent covariates given mean, sd, and prevalence
In kaz-yos/distributed: Examine Privacy Preserving Data Analysis Methods in Simulated Distributed Data Network
Description
Usage
Arguments
Value
Author(s)
View source: R/01.GenerateData.R
Description
The first covariate is a Normal(mean1, sd1) random variable, whereas the other
covariates are Bernoulli(p) random variables where p's are specified by the
elements of the pp vector.
Usage
1
AssignCovariatesNormBin(n, mean1, sd1, pp)
Arguments
n
number of individuals to create
mean1
mean for first continuous normal covariate
sd1
sd for first continuous normal covariate
pp
vector of prevalences for other Bernoulli covariates
Value
n x (m+1) data frame including ID and m covariates
Author(s)
Kazuki Yoshida
kaz-yos/distributed documentation built on May 27, 2019, 4:50 a.m.
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Description Usage Arguments Value Author(s)
View source: R/01.GenerateData.R
Description
The first covariate is a Normal(mean1, sd1) random variable, whereas the other covariates are Bernoulli(p) random variables where p's are specified by the elements of the pp vector.
Usage
1 | AssignCovariatesNormBin(n, mean1, sd1, pp)
|
Arguments
n |
number of individuals to create |
mean1 |
mean for first continuous normal covariate |
sd1 |
sd for first continuous normal covariate |
pp |
vector of prevalences for other Bernoulli covariates |
Value
n x (m+1) data frame including ID and m covariates
Author(s)
Kazuki Yoshida
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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