horvitzThompson: Compute the Horvitz-Thompson Estimator
Description
Calculate the Horvitz-Thompson Estimator for a finite population mean/proportion or total based on sample data collected from a complex sampling design.
Usage
horvitzThompson(y, pi = NULL, N = NULL, pi2 = NULL,
var_est = FALSE, var_method = "lin_HB", B = 1000, strata = NULL)
Arguments
y
A numeric vector of the sampled response 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 "lin_HT" 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: "lin_HB"= Hajek-Berger estimator, "lin_HH" = Hansen-Hurwitz estimator, "lin_HTSRS" = Horvitz-Thompson estimator under simple random sampling without replacement, and "lin_HT" = Horvitz-Thompson estimator or a resampling technique: "bootstrap_SRS" = bootstrap variance estimator under simple random sampling without replacement. The default is "lin_HB".
B
The number of bootstrap samples if computing the bootstrap variance estimator. Default is 1000.
strata
A factor vector of the stratum membership. If NULL, all units are put into the same stratum. Must have same length as y.
Value
A list of output containing:
pop_total: Estimate of population total
pop_mean: Estimate of the population mean
pop_total_var: Estimated variance of population total estimate
pop_mean_var: Estimated variance of population mean estimate