A version of glmerControl from lme4, with different defaults.
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", ...)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.
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.
character - rules for
checking whether all random effects have >= 5 levels.
See action.
character - rules for checking
whether all random effects have > 1 level. See action.
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.
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.
character - check for problematic scaling of columns of fixed-effect model matrix, e.g. parameters measured on very different scales.
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
character - check that the response is not constant.
other arguments to glmerControl