use_generalised_linear_mixed_model: Function for generalised linear mixed model

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

Description

Function for generalised linear mixed model

Usage

use_generalised_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,
  family,
  link,
  package_mixed_model
)

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
family,	family of distributions for the response variable
link,	link function for the variances
package_mixed_model	package to be used for mixed model

Value

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

Examples

datafile <- system.file("extdata", "culcita_data.csv",
package = "packDAMipd")
dataset <- read.csv(datafile)
results1 = use_generalised_linear_mixed_model("predation",
dataset = datafile,fix_eff = c("ttt"), family = "binomial",
fix_eff_interact_vars = NULL, random_intercept_vars = c("block"),
nested_intercept_vars_pairs = NULL, cross_intercept_vars_pairs = NULL,
uncorrel_slope_intercept_pairs = NULL, random_slope_intercept_pairs = NULL,
 link = NA, package_mixed_model = NA)
 

packDAMipd documentation built on March 3, 2021, 5:07 p.m.