packDAMipd (version 1.1.0)

form_expression_mixed_model_lme4: Form expression to use with mixed models

Description

Form expression to use with mixed models

Usage

form_expression_mixed_model_lme4(
  param_to_be_estimated,
  dataset,
  fix_eff,
  fix_eff_interact_vars,
  random_intercept_vars,
  nested_intercept_vars_pairs,
  cross_intercept_vars_pairs,
  uncorrel_slope_intercept_pairs,
  random_slope_intercept_pairs,
  family,
  link
)

Value

result regression result with plot if success and -1, if failure

Arguments

param_to_be_estimated,

column name of dependent variable

dataset,

a dataframe

fix_eff,

names of variables as fixed effect predictors

fix_eff_interact_vars,

if interaction -true

random_intercept_vars,

names of variables for random intercept

nested_intercept_vars_pairs,

those of the random intercept variables with nested effect

cross_intercept_vars_pairs,

those of the random intercept variables with crossed effect

uncorrel_slope_intercept_pairs,

variables with correlated intercepts

random_slope_intercept_pairs,

random slopes intercept pairs - this is a list of paired variables

family,

family of distribution for non gaussian distribution of predicted variable

link,

link function for the variance

Details

Form the expression for mixed model

Examples

# \donttest{
datafile <- system.file("extdata", "data_linear_mixed_model.csv",
package = "packDAMipd")
dt = utils::read.csv(datafile, header = TRUE)
formula <- form_expression_mixed_model_lme4("extro",
  dataset = dt,
  fix_eff = c("open", "agree", "social"),
  fix_eff_interact_vars = NULL,
  random_intercept_vars = c("school", "class"),
  nested_intercept_vars_pairs = list(c("school", "class")),
  cross_intercept_vars_pairs = NULL,
  uncorrel_slope_intercept_pairs = NULL,
  random_slope_intercept_pairs = NULL, family = "binomial", link = NA
)
# }