gof.lmm.O.test.norefit: Goodness-of fit test for LMM

In rokblagus/gofLMM: Goodness-of-fit for linear mixed effects model (gofLMM)

Goodness-of fit test for LMM

Description

Goodness-of fit test based on cumulative sum stochastic process for O using non-diagonal blocked matrices A and B, simulation approach where refitting is not necessary.

Usage

gof.lmm.O.test.norefit(
  fit,
  residuals = "individual",
  std.type = c(1, 2),
  use.correction.for.imbalance = FALSE,
  type = c("sign.flip", "normal", "normal.m"),
  M = 100,
  verbose = FALSE
)

Arguments

fit	The result of a call to "nlme". The model must be fitted with control=lmeControl( returnObject = TRUE) and keep.data=TRUE. An error message is returned otherwise. ID variable must be numeric and ordered from 1:N ! Canno't use transofrmations of the outcome variable directly in the formula i.e. lme(sqrt(y)~x) will return p=1!
residuals	Residuals to be used when constructing the process.
std.type	Type of standardization to be used for the residuals when constructing the process. Currently implemeneted options are 1 and 2 for $S_i=\hat\sigma^-1/2I_n_i$ and $S_i=\hatV_i^-1/2$.
use.correction.for.imbalance	Logical. use $n_i^-1/2 S_i$ when standardizing the residuals. Defaults to FALSE.
type	How to obtain the processes $W^m$. Possible values are "sign.flip" for the sign-flipping random matrix, "normal" for the standard normal (same for all within cluster), "normal.m" for the standard normal (different for all within cluster).
M	Number of random simulations/sign-flipps. Defaults to 100.
verbose	Logical. Print the current status of the test. Can slow down the algorithm, but it can make it feel faster. Defaults to FALSE.

Author(s)

Rok Blagus, [e-mail]

See Also

gof.lmm

rokblagus/gofLMM documentation built on April 4, 2022, 8:41 p.m.