packDAMipd (version 1.1.0)

use_linear_mixed_model: Function for mixed effect regression

Description

Function for mixed effect regression

Usage

use_linear_mixed_model(
  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,
  package_mixed_model
)

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,

those of the fixed effect predictors that show interaction

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 no correlated intercepts

random_slope_intercept_pairs,

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

package_mixed_model

package to be used for mixed model

Examples

# \donttest{
datafile <- system.file("extdata", "data_linear_mixed_model.csv",
package = "packDAMipd")
dataset = utils::read.table(datafile, header = TRUE, sep = ",",
na.strings = "NA",
dec = ".", strip.white = TRUE)
result <- use_linear_mixed_model("extro",
  dataset = dataset,
  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, package_mixed_model = NA)
# }