permDif: Test the difference of the network connectivity between two...
In PeterVerboon/lagnetw: The package builds a network for ESM data

Description Usage Arguments Value Examples

The predictors are the variables specified in "vars=", with "L1" added to the name. Note that these variables must exist in the data.

permDif(
  dat,
  vars,
  covs = NULL,
  group,
  subjnr,
  randomVars = NULL,
  subset = NULL,
  type = "lagged",
  perms = 50,
  optim = "bobyqa"
)

`dat`	data frame
`vars`	vector with the names of the dependent variables.
`covs`	vector with the names of the covariates.
`group`	dichotomous variable that indicates the two groups to be compared
`subjnr`	identification number of the subjects
`randomVars`	vector, indicating which variables should be included as random effects. If "all" then all fixed effects are taken. If "null" only intercept is used as random effect.
`subset`	subset of predictor variables which are compared in summary statistics. If null then result is also null.
`type`	type of analyses: lagged ("lagged") or contemporaneous predictors ("contemp")
`perms`	number of permutations.
`optim`	optimizer used in lmer, options: "bobyqa" or "Nelder_Mead", see lmerControl (lme4)

Estimate of difference between groups wrt network connectivity with p value based on permutations. and permutation distribution. The p-values for differences of all individual paths and of summaries are given. Also p-values for the differences of the centrality measures inDegree and outDegree are given.

1 2 3 4	data("gratitude") vars <- c("pa_1","pa_2","pa_3","na_1","na_2","na_3") out <- permDif(dat=gratitude,vars=vars, group="wellBeing", subjnr="subjnr", randomVars = FALSE, perms = 10)