Nothing
# Help-functions
data_frame <- function(...) {
x <- data.frame(..., stringsAsFactors = FALSE)
rownames(x) <- NULL
x
}
is_merMod <- function(fit) {
inherits(fit, c("lmerMod", "glmerMod", "nlmerMod", "merModLmerTest"))
}
is_stan_model <- function(fit) {
inherits(fit, c("stanreg", "stanfit", "brmsfit"))
}
#' @importFrom sjmisc str_contains
get_glm_family <- function(fit) {
c.f <- class(fit)
# do we have glm? if so, get link family. make exceptions
# for specific models that don't have family function
if (any(c.f %in% c("lme", "plm"))) {
fitfam <- ""
logit_link <- FALSE
} else {
fitfam <- stats::family(fit)$family
logit_link <- stats::family(fit)$link == "logit"
}
# create logical for family
binom_fam <- fitfam %in% c("binomial", "quasibinomial")
poisson_fam <- fitfam %in% c("poisson", "quasipoisson") ||
sjmisc::str_contains(fitfam, "negative binomial", ignore.case = T)
list(is_bin = binom_fam, is_pois = poisson_fam, is_logit = logit_link)
}
# return names of objects passed as ellipses argument
dot_names <- function(dots) unname(unlist(lapply(dots, as.character)))
#' @importFrom tidyr nest
#' @importFrom dplyr select filter group_vars
#' @importFrom stats complete.cases
#' @importFrom rlang .data
get_grouped_data <- function(x) {
# retain observations that are complete wrt grouping vars, then nest
grps <- x %>%
dplyr::group_modify(~ dplyr::filter(.x, stats::complete.cases(.y))) %>%
tidyr::nest()
# arrange data
if (length(dplyr::group_vars(x)) == 1)
reihe <- order(grps[[1]])
else
reihe <- order(grps[[1]], grps[[2]])
grps <- grps[reihe, ]
grps
}
.compact_character <- function(x) {
x[!sapply(x, function(i) is.null(i) || nchar(i) == 0 || is.na(i) || any(i == "NULL", na.rm = TRUE))]
}
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