clust.lm: dispatch to one of the implemented cluster methods
In brentp/clustermodelr: Models on clusters of correlated data

Description Usage Arguments

For every method except mixed_model, one or more of the arguments must be specified. To run a linear model, simply send the formula in lme4 syntax

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clust.lm(formula, covs, meth, weights = NULL, gee.corstr = NULL,
  gee.idvar = NULL, counts = FALSE, bumping = FALSE, combine = c(NA,
  "liptak", "z-score"), skat = FALSE)

`formula`	an R formula containing "methylation"
`covs`	covariate data.frame containing the terms in formula except "methylation" which is added automatically
`meth`	a matrix of correlated data.
`weights`	matrix of weights with same dim as of rows as `meth` or NULL. Used in weighted regression.
`gee.corstr`	if specified, the the corstr arg to geeglm. gee.idvar must also be specified.
`gee.idvar`	if specified, the cluster variable to geeglm
`counts`	if specified, then use poisson or NB where available
`bumping`	if true then the bumping algorithm is used.
`combine`	either "liptak" or "z-score" used to get a single p-value after running a test on each probe.
`skat`	use the SKAT method to test associated. In this case, the model will look like: `disease ~ 1` and it will be tested against the methylation matrix