gof.lmm.O.test.type2: Goodness-of fit test for LMM

View source: R/functions_gofLMM.R

gof.lmm.O.test.type2R Documentation

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. I am not reestimating A and B and always ordering by the original fitted values!

Usage

gof.lmm.O.test.type2(
  fit,
  residuals = "individual",
  std.type = c(1, 2),
  use.correction.for.imbalance = FALSE,
  type = c("sign.flip", "permutation"),
  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 approach and "permutation" for the permutation approach.

M

Number of random simulations/sign-flipps/permutations. 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, rok.blagus@mf.uni-lj.si

See Also

gof.lmm


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