set_lme4_control: Control of Mixed Model Fitting

Description Usage Arguments

Description

A version of glmerControl from lme4, with different defaults.

Usage

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set_lme4_control(check.nobs.vs.rankZ = "ignore",
  check.nobs.vs.nlev = "ignore", check.nlev.gtreq.5 = "ignore",
  check.nlev.gtr.1 = "ignore", check.nobs.vs.nRE = "ignore",
  check.rankX = c("message+drop.cols", "silent.drop.cols",
  "warn+drop.cols", "stop.deficient", "ignore"),
  check.scaleX = "warning", check.formula.LHS = "stop",
  check.response.not.const = "ignore", ...)

Arguments

check.nobs.vs.rankZ

character - rules for checking whether the number of observations is greater than (or greater than or equal to) the rank of the random effects design matrix (Z), usually necessary for identifiable variances. As for action, with the addition of "warningSmall" and "stopSmall", which run the test only if the dimensions of Z are < 1e6. nobs > rank(Z) will be tested for LMMs and GLMMs with estimated scale parameters; nobs >= rank(Z) will be tested for GLMMs with fixed scale parameter. The rank test is done using the method="qr" option of the rankMatrix function.

check.nobs.vs.nlev

character - rules for checking whether the number of observations is less than (or less than or equal to) the number of levels of every grouping factor, usually necessary for identifiable variances. As for action. nobs<nlevels will be tested for LMMs and GLMMs with estimated scale parameters; nobs<=nlevels will be tested for GLMMs with fixed scale parameter.

check.nlev.gtreq.5

character - rules for checking whether all random effects have >= 5 levels. See action.

check.nlev.gtr.1

character - rules for checking whether all random effects have > 1 level. See action.

check.nobs.vs.nRE

character - rules for checking whether the number of observations is greater than (or greater than or equal to) the number of random-effects levels for each term, usually necessary for identifiable variances. As for check.nobs.vs.nlev.

check.rankX

character - specifying if rankMatrix(X) should be compared with ncol(X) and if columns from the design matrix should possibly be dropped to ensure that it has full rank. Sometimes needed to make the model identifiable. The options can be abbreviated; the three "*.drop.cols" options all do drop columns, "stop.deficient" gives an error when the rank is smaller than the number of columns where "ignore" does no rank computation, and will typically lead to less easily understandable errors, later.

check.scaleX

character - check for problematic scaling of columns of fixed-effect model matrix, e.g. parameters measured on very different scales.

check.formula.LHS

check whether specified formula has a left-hand side. Primarily for internal use within simulate.merMod; use at your own risk as it may allow the generation of unstable merMod objects

check.response.not.const

character - check that the response is not constant.

...

other arguments to glmerControl


glmmsr documentation built on May 2, 2019, 2:12 p.m.