survey_mle: Compute proportion in the survey sample (standard estimator)
In pempi: Proportion Estimation with Marginal Proxy Information

survey_mle

R Documentation

Compute proportion in the survey sample (standard estimator)

Description

Proportion estimated using the survey sample and confidence intervals based on the Clopper-Pearson and the standard asymptotic approach.

Usage

survey_mle(R, n, pi0 = 0, alpha = 0, beta = 0, gamma = 0.05, V = NULL, ...)

Arguments

`R`	A `numeric` that provides the people of positive people in the sample.
`n`	A `numeric` that provides the sample size.
`pi0`	A `numeric` that provides the prevalence or proportion of people (in the whole population) who are positive, as measured through a non-random, but systematic sampling (e.g. based on medical selection). Default value is `0` and in this case this information is not used in the estimation procedure.
`alpha`	A `numeric` that provides the False Negative (FN) rate for the sample R. Default value is `0`.
`beta`	A `numeric` that provides the False Positive (FP) rate for the sample R. Default value is `0`.
`gamma`	A `numeric` that is used to compute a (1 - gamma) confidence region for the proportion. Default value is `0.05`.
`V`	A `numeric` that corresponds to the average of squared sampling weights. Default value is `NULL`.
`...`	Additional arguments.

Value

A cpreval object with the structure:

estimate: Estimated proportion.
sd: Estimated standard error of the estimator.
ci_asym: Asymptotic confidence interval at the 1 - gamma confidence level.
gamma: Confidence level (i.e. 1 - gamma) for confidence intervals.
method: Estimation method (in this case sample survey).
measurement: A vector with (alpha0, alpha, beta).
boundary: A boolean variable indicating if the estimates falls at the boundary of the parameter space.
pi0: Value of pi0 (input value).
sampling: Type of sampling considered ("random" or "weighted").
V: Average sum of squared sampling weights if weighted/stratified is used (otherwise NULL).
...: Additional parameters.

Author(s)

Stephane Guerrier, Maria-Pia Victoria-Feser, Christoph Kuzmics

Examples

# Samples without measurement error
X = sim_Rs(theta = 30/1000, pi0 = 10/1000, n = 1500, seed = 18)
survey_mle(R = X$R, n = X$n)

# With measurement error
X = sim_Rs(theta = 30/1000, pi0 = 10/1000, n = 1500, alpha = 0.01, beta = 0.05, seed = 18)
survey_mle(R = X$R, n = X$n)
survey_mle(R = X$R, n = X$n, alpha = 0.01, beta = 0.05)

pempi documentation built on Oct. 9, 2023, 5:10 p.m.