rlmer: Robust linear mixed models

Description

Robust estimation of linear mixed effects models, for hierarchical nested and non-nested, e.g., crossed, datasets.

The lmerNoFit function can be used to get trivial starting values. This is mainly used to verify the algorithms to reproduce the fit by lmer when starting from trivial initial values.

Usage

rlmer(formula, data, ..., method = "DAStau",
    rho.e = smoothPsi, rho.b = smoothPsi, rho.sigma.e,
    rho.sigma.b, rel.tol = 1e-08,
    max.iter = 40 * (r + 1)^2, verbose = 0, doFit = TRUE,
    init)
  lmerNoFit(..., initTheta)

Arguments

formula

a two-sided linear formula object describing the fixed-effects part of the model, with the response on the left of a ~ operator and the terms, separated by + operators, on the right. The vertical bar character "|"

data

an optional data frame containing the
  variables named in formula.  By default the
  variables are taken from the environment from which
  lmer is called.

...

Additional parameters passed to lmer to find
  the initial estimates. See lmer.

method

method to be used for estimation of theta
  and sigma, see Details.

rho.e

object of class psi_func, specifying the
  functions to use for the huberization of the residuals.

rho.b

object of class psi_func or list of such
  objects (see Details), specifying the functions to use
  for the huberization of the random effects.

rho.sigma.e

object of class psi_func, specifying
  the weight functions to use for the huberization of the
  residuals when estimating the variance components, use
  the psi2propII function to specify squared
  weig

rho.sigma.b

(optional) object of class psi_func or
  list of such objects, specifying the weight functions to
  use for the huberization of the random effects when
  estimating the variance components (see Details). Use
  psi2

rel.tol

relative tolerance used as criteria in the
  fitting process.

max.iter

maximum number of iterations allowed.

verbose

verbosity of output. Ranges from 0 (none)
  to 3 (a lot of output)

doFit

logical scalar. When doFit = FALSE
  the model is not fit but instead a structure with the
  model matrices for the random-effects terms is returned
  (used to speed up tests). When doFit = TRUE, the
  default, the model is fit i

init

optional lmerMod- or rlmerMod-object to use
  for starting values, a list with elements fixef,
  u, sigma, theta, or a function
  producing an lmerMod object.

initTheta

parameter to initialize theta with
  (optional)

`Value`

object of class rlmerMod.

`Details`

[object Object],[object Object],[object Object],[object Object]

`See Also`

lmer, vignette("rlmer")

`Examples`

Run this code## dropping of VC
system.time(rlmer(Yield ~ (1|Batch), Dyestuff2, method="DASvar"))

## Default method "DAStau"
  system.time(rfm.DAStau <- rlmer(Yield ~ (1|Batch), Dyestuff))
  summary(rfm.DAStau)
  ## DASvar method (faster, less accurate)
  system.time(rfm.DASvar <- rlmer(Yield ~ (1|Batch), Dyestuff,
                                  method="DASvar"))
  ## compare the two
  compare(rfm.DAStau, rfm.DAStau)

  ## Fit variance components with higher efficiency
  ## psi2propII yields squared weights to get robust estimates
  rlmer(diameter ~ 1 + (1|plate) + (1|sample), Penicillin,
        rho.sigma.e = psi2propII(smoothPsi, k = 2.28),
        rho.sigma.b = psi2propII(smoothPsi, k = 2.28))

  ## use chgDefaults for variance components including
  ## correlation terms (regular, non squared weights suffice)
  rlmer(Reaction ~ Days + (Days|Subject), sleepstudy,
        rho.sigma.e = psi2propII(smoothPsi, k = 2.28),
        rho.sigma.b = chgDefaults(smoothPsi, k = 5.11, s=10))
rlmer(Yield ~ (1|Batch), Dyestuff, init = lmerNoFit)
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