use_seemingly_unrelated_regression: Bivariate regression for correlated observations

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

Description

Bivariate regression for correlated observations

Usage

use_seemingly_unrelated_regression(
  param1_to_be_estimated,
  param2_to_be_estimated,
  dataset,
  indep_var,
  covariates1,
  covariates2,
  interaction1,
  interaction2
)

Arguments

param1_to_be_estimated	parameter of interest
param2_to_be_estimated	parameter of interest
dataset	data set to be provided
indep_var	the independent variable (column name in data file)
covariates1	list of covariates - for equation 1
covariates2	list of covariates - for equation 2
interaction1	boolean value to indicate interaction - for equation 1
interaction2	boolean value to indicate interaction - for equation 2 false by default

Value

the results of the regression analysis

Examples

datafile <- system.file("extdata", "sureg_data.csv", package = "packDAMipd")
dataset <- read.csv(datafile, stringsAsFactors = TRUE)
results_sureg <- use_seemingly_unrelated_regression("read", "math",
  dataset = dataset,
  indep_var = "female", covariates1 = c("as.numeric(ses)", "socst"),
  covariates2 = c("as.numeric(ses)", "science"), interaction1 = FALSE,
  interaction2 = FALSE
)

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