form_expression_mixed_model_lme4: Form expression to use with mixed models

In packDAMipd: Decision Analysis Modelling Package with Parameters Estimation Ability from Individual Patient Level Data

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
)

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

Value

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

Examples

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
)

packDAMipd documentation built on May 29, 2024, 3:18 a.m.