ratioEstimator: Compute a ratio estimator

In Swarthmore-Statistics/mase: Model-Assisted Survey Estimators

Compute a ratio estimator

Description

Calculates a ratio estimator for a finite population mean/proportion or total based on sample data collected from a complex sampling design and auxiliary population data.

Usage

ratioEstimator(
  y,
  xsample,
  xpop,
  datatype = "raw",
  pi = NULL,
  N = NULL,
  pi2 = NULL,
  var_est = FALSE,
  var_method = "LinHB",
  B = 1000,
  fpc = TRUE,
  messages = TRUE
)

Arguments

y	A numeric vector of the sampled response variable.
xsample	A numeric vector of the sampled auxiliary variable.
xpop	A numeric vector of population level auxiliary information. Must come in the form of raw data, population total or population mean.
datatype	A string that specifies the form of population auxiliary data. The possible values are "raw", "total" or "mean". If datatype = "raw", then xpop must contain a numeric vector of the auxiliary variable for each unit in the population. If datatype = "total" or "mean", then contains either the population total or population mean for the auxiliary variable.
pi	A numeric vector of inclusion probabilities for each sampled unit in y. If NULL, then simple random sampling without replacement is assumed.
N	A numeric value of the population size. If NULL, it is estimated with the sum of the inverse of the pis.
pi2	A square matrix of the joint inclusion probabilities. Needed for the "LinHT" variance estimator.
var_est	A logical indicating whether or not to compute a variance estimator. Default is FALSE.
var_method	The method to use when computing the variance estimator. Options are a Taylor linearized technique: "LinHB"= Hajek-Berger estimator, "LinHH" = Hansen-Hurwitz estimator, "LinHTSRS" = Horvitz-Thompson estimator under simple random sampling without replacement, and "LinHT" = Horvitz-Thompson estimator or a resampling technique: "bootstrapSRS" = bootstrap variance estimator under simple random sampling without replacement. The default is "LinHB".
B	The number of bootstrap samples if computing the bootstrap variance estimator. Default is 1000.
fpc	Default to TRUE, logical for whether or not the variance calculation should include a finite population correction when calculating the "LinHTSRS" or the "SRSbootstrap" variance estimator.
messages	A logical indicating whether to output the messages internal to mase. Default is TRUE.

Value

List of output containing:

* pop_total: Estimate of population total.

* pop_mean: Estimate of population mean.

* pop_total_var: Estimated variance of population total estimate.

* pop_mean_var: Estimated variance of population mean estimate.

References

\insertRef

coc77mase \insertRefsar92mase

Examples

library(dplyr)
data(IdahoPop)
data(IdahoSamp)

xsample <- filter(IdahoSamp, COUNTYFIPS == "16055")
xpop <- filter(IdahoPop, COUNTYFIPS == "16055")

ratioEstimator(y = xsample$BA_TPA_ADJ,
               xsample = xsample$tcc,
               xpop = xpop$tcc,
               datatype = "means",
               N = xpop$npixels)

Swarthmore-Statistics/mase documentation built on March 5, 2024, 6:16 a.m.