SteppedPower (version 0.1.0)

construct_CovMat: Construct a Covariance Matrix

constructs a (block diagonal) covariance matrix. This function calls `construct_CovBlk` (or `construct_CovSubMat` in case of repeated observations of the same individuals) for each block.

Description

Construct a Covariance Matrix

constructs a (block diagonal) covariance matrix. This function calls `construct_CovBlk` (or `construct_CovSubMat` in case of repeated observations of the same individuals) for each block.

Usage

construct_CovMat(
  SumCl = NULL,
  timepoints = NULL,
  sigma,
  tau,
  eta = NULL,
  tauAR = NULL,
  etaAR = NULL,
  rho = NULL,
  gamma = NULL,
  trtMat = NULL,
  N = NULL,
  CovBlk = NULL,
  psi = NULL,
  INDIV_LVL = FALSE
)

Arguments

SumCl

total number of clusters

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, residual error of cluster means if no N given.

tau

numeric, standard deviation of random intercepts

eta

numeric (scalar or matrix), standard deviation of random slopes. If `eta` is given as scalar, `trtMat` is needed as well.

tauAR

numeric (scalar), value between 0 and 1. Defaults to NULL. If `tauAR` is not NULL, the random intercept `tau` is AR1-correlated. *Currently not compatible with `rho`!=0 !*

etaAR

numeric (scalar), value between 0 and 1. Defaults to NULL. If `etaAR` is not NULL, the random slope `eta` is AR1-correlated. *Currently not compatible with `rho`!=0 !*

rho

numeric (scalar), correlation of `tau` and `eta`

gamma

numeric (scalar), random time effect

trtMat

a matrix of dimension *#Cluster* x *timepoints* as produced by the function `construct_trtMat`, indicating the cluster-periods that receive interventional treatment. Defaults to NULL. If trtMat is given, the arguments `SumCl` and `timepoints` are ignored (!).

N

numeric, number of individuals per cluster. Either a scalar, vector of length #Clusters or a matrix of dimension #Clusters x timepoints. Defaults to 'rep(1,sum(Cl))' if not passed.

CovBlk

a matrix of dimension *timepoints* x *timepoints*.

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 covariance matrix

Examples

# NOT RUN {
## Two clusters, three timepoints,
## residual standard error sd=3, random slope sd=1.
construct_CovMat(SumCl=2, timepoints=3, sigma=3, tau=1)
##
##
## ... with random slope as AR-1 process
construct_CovMat(SumCl=2, timepoints=3, sigma=3, tau=1, tauAR=.8)
##
##


## ... with sigma and tau variing over time and between clusters:
construct_CovMat(SumCl=2,timepoints=3,
                 sigma=matrix(c(1,2,2,1,1,2),nrow=2, byrow=TRUE),
                 tau=matrix(c(.2,.1,.1,.2,.2,.1),nrow=2, byrow=TRUE),
                 N=c(3,4))
# }