construct_CovSubMat: Construct a Block of the Covariance Matrix

In PMildenb/SteppedPower: Power Calculation for Stepped Wedge Designs

Construct a Block of the Covariance Matrix

Description

Constructs the covariance matrix for multiple measurements of the same cluster if the same individuals are observed at all time periods. This function is not designed to be used directly.

Usage

construct_CovSubMat(
  N,
  timepoints,
  sigma,
  tau,
  eta = NULL,
  AR = NULL,
  rho = NULL,
  gamma = NULL,
  psi = NULL,
  INDIV_LVL = FALSE
)

Arguments

N	Number of individuals per cluster
timepoints	numeric (scalar or vector), number of timepoints (periods). If design is swd, timepoints defaults to length(Cl)+1. Defaults to 1 for parallel designs.
sigma	numeric (vector of length 'timepoints'), residual error
tau	numeric (vector of length 'timepoints'), standard deviation of random intercepts
eta	numeric (vector of length 'timepoints'), standard deviation of random slope
AR	numeric, vector containing up to three values, each between 0 and 1. Defaults to NULL. It defines the AR(1)-correlation of random effects. The first element corresponds to the cluster intercept, the second to the treatment effect and the third to subject specific intercept. If only one element is provided, autocorrelation of all random effects is assumed to be the same. *Currently not compatible with 'rho'!=0 !*
rho	numeric (scalar), correlation of 'tau' and 'eta'. The default is no correlation.
gamma	numeric (vector of length 'timepoints'), standard deviation of a random time effect.
psi	numeric (scalar), random subject specific intercept. Leads to a closed cohort setting
INDIV_LVL	logical, should the computation be conducted on an individual level? This leads to longer run time and is mainly for diagnostic purposes.

Value

a block of a covariance matrix with two levels of clustering, corresponding to intra-cluster covariance over time for one cluster

PMildenb/SteppedPower documentation built on Sept. 20, 2023, 4:57 a.m.