permutes: clusterperm.lm – R documentation

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clusterperm.lm

Cluster-based permutation tests for time series data, based on mixed-effects models or other buildmer models. This is an alias for clusterperm.lmer, except that random effects are explicily disallowed.

Description

Cluster-based permutation tests for time series data, based on mixed-effects models or other buildmer models. This is an alias for clusterperm.lmer, except that random effects are explicily disallowed.

Usage

clusterperm.lm(
  formula,
  data = NULL,
  family = gaussian(),
  weights = NULL,
  offset = NULL,
  series.var,
  buildmerControl = list(direction = "order", crit = "LRT", quiet = TRUE, ddf = "lme4"),
  nperm = 1000,
  type = "regression",
  parallel = FALSE,
  progress = "none"
)

Arguments

`formula`	A normal formula without random effects. This can also be a buildmer terms object, provided `dep` is passed in `buildmerControl`. Only a single response variable is supported. For binomial models, the `cbind` syntax is not supported; please convert your dependent variable to a proportion and use weights instead.
`data`	The data.
`family`	The family.
`weights`	An optional vector of prior case weights. This vector is evaluated in the calling environment, not in the formula or data frame!
`offset`	An optional vector containing a prior offset term. This vector is evaluated in the calling environment, not in the formula or data frame!
`series.var`	A one-sided formula giving the variable grouping the time series.
`buildmerControl`	Options overriding the defaults in `buildmerControl`.
`nperm`	The number of permutations.
`type`	A character string of either `'anova'` or `'regression'`. The former runs an analysis of variance and returns F-values and p-values based on the explained variance of each factor in the design. The latter runs a linear-regression analysis and returns t-values and p-values based on individual effects. When running ANOVA, it is advised to use orthogonal predictors, as type III sums of squares are used.
`parallel`	Whether to parallelize the permutation testing using plyr's `parallel` option. Needs some additional set-up; see the plyr documentation.
`progress`	A plyr `.progress` bar name, see the plyr documentation. If not `'none'` while `parallel=TRUE`, an ad-hoc solution will be used, which will be visible if the cluster nodes were created with `outfile=''`.

Details

If not explicitly overridden in the buildmerControl argument, the function changes a few buildmer defaults to make more sense for permutation testing. This includes setting direction='order' and quiet=TRUE. Set these options explicitly to override this behavior. Because model comparisons are used for efficient permutation testing, REML is not supported. Omega squared is not available for mixed-effects ANOVA; the w2 column will not be included in the resulting permutes object. The returned object provides the raw bootstrap samples in the pb attribute. These are used to compute a corrected p-value using Maris & Oostenveld's (2007) cluster mass statistic, but can also be used by the user to compute other such statistics. These obviously significantly increase the size of the R object; if this becomes a problem, there is no harm in deleting them using e.g. attr(x,'perms') <- NULL.

Value

A data frame.

Examples

perms <- clusterperm.lm(Fz ~ Deviant * Session,data=MMN,series.var=~Time)

permutes

Permutation Tests for Time Series Data

v2.0.1

FreeBSD

Authors

Cesko C. Voeten [aut, cre]

Initial release