MR: Regression Composite estimation

In DanielBonnery/CompositeRegressionEstimation: X

Description

Regression Composite estimation

Usage

MR(
  list.tables,
  w,
  id,
  list.xMR = NULL,
  list.x1 = NULL,
  list.x2 = NULL,
  list.y = NULL,
  calibmethod = "linear",
  Alpha = 0.75,
  theta = 3/4,
  list.dft.x2 = NULL,
  dft0.xMR = NULL,
  mu0 = NULL,
  Singh = TRUE,
  dispweight = FALSE,
  analyse = FALSE
)

Arguments

list.tables	A list of dataframes
w	either a real number of a character string indicating the name of the weight variable.
id	an identifier
list.xMR	list of variables used to compute proxy composite regression variable
list.x1	list of auxiliary variables used in the cablibration, whose calibrated weighted total has to be equal to initially weithed total
list.x2	id list of auxiliary variables used in the cablibration, whose calibrated weighted total has to be equal to values provided by list.dft.x2
Alpha	a vector of alpha values. if alpha="01", this will compute MR3
theta	a numerical value
list.dft.x2	id list of auxiliary variables used in the cablibration, whose calibrated weighted total has to be equal to initially weithed total
mu0	a numerical value
Singh	a boolean
dispweight	a boolean
analyse	a boolean
list.y:	list of variables whose weighted sum needs to be computed. It can be factor or character variables.

Value

a dataframe.

Examples

MR(list.tables<-
plyr::dlply(CRE_data,.variables=~time),w="Sampling.weight",list.xMR="Status",id="Identifier",list.y=c("Hobby","Status","State"))$dfEst;

DanielBonnery/CompositeRegressionEstimation documentation built on June 17, 2020, 12:16 p.m.