mvrnorm_corr_gen {microbiomeDASim}R Documentation

Generate Multivariate Random Normal Longitudinal Data

Description

For this methodology we assume that we draw a set of n independent each with q_{i} observations.

Usage

mvrnorm_corr_gen(n, obs, mu, sigma, rho, corr_str = c("ar1", "compound",
  "ind"), zero_trunc = TRUE)

Arguments

n

integer scalar representing the total number of individuals

obs

integer or vector specifying the number of observations per indivdiual. If an integer then all indivdiuals are assummed to have the same number of obsevations. If a vector, then the vector must have length equal to n where each element specifies the number of observations for the i^{th} individual.

mu

integer or vector specifying the mean value for individuals. If an integer then all indivdiuals are assummed to have the same mean. If a vector, then the vector must have length equal to n where each element specifies the mean for the i^{th} individual.

sigma

numeric scalar or vector specifying the standard deviation for observations.

rho

numeric scalar value between [0, 1] specifying the amount of correlation between. assumes that the correlation is consistent for all subjects.

corr_str

character value specifying the correlation structure. Currently available methods are 'ar1', 'compound', and 'ind' which correspond to first-order autoregressive, compound or equicorrelation, and independence respecitvely.

zero_trunc

logical value to specifying whether the generating distribution should come from a multivariate zero truncated normal or an untruncated multivariate normal. by default we assume that zero truncation occurs since this is assummed in our microbiome setting.

Value

This function returns a list with the following objects:

df - data.frame object with complete outcome Y, subject ID, time, group, and outcome with missing data

Y - vector of complete outcome

Mu - vector of complete mean specifications used during simulation

Sigma - block diagonal symmetric matrix of complete data used during simulation

N - total number of observations

Examples

mvrnorm_corr_gen(n=15, obs=4, mu=20, sigma=2, rho=0.9, corr_str="ar1")


[Package microbiomeDASim version 1.0.0 Index]