Unequal probability sampling from a finite population: A multicriteria approach

Bayesian inference for finite population quantiles from unequal probability samples.

This paper develops two Bayesian methods for inference about finite population quantiles of continuous survey variables from unequal probability sampling. The first method estimates cumulative distribution functions of the continuous survey variable by fitting a number of probit penalized spline regression models on the inclusion probabilities. The finite population quantiles are then obtained ...

Bayesian penalized spline model-based inference for finite population proportion in unequal probability sampling.

We propose a Bayesian Penalized Spline Predictive (BPSP) estimator for a finite population proportion in an unequal probability sampling setting. This new method allows the probabilities of inclusion to be directly incorporated into the estimation of a population proportion, using a probit regression of the binary outcome on the penalized spline of the inclusion probabilities. The posterior pre...

Predicting Random Effects from a Finite Population of Unequal Size Clusters based on Two-Stage Sampling

Prediction of random effects is an important problem with expanding applications. In the simplest context, the problem corresponds to prediction of the latent value (the mean) of a realized cluster selected via two-stage sampling. Best linear unbiased predictors developed from mixed models are widely used, but their development requires distributional assumptions or an infinite population frame...

Non-response in Sampling from a Dichotomous Finite Population Non-response in Sampling from a Dichotomous Finite Population (^223^66)

A decision theoretic approach to Imputation in finite population sampling

SUMMARY Consider the situation where observations are missing at random from a simple random sample drawn from a finite population. In certain cases it is of interest to create a full set of sample values such that inferences based on the full set will have the stated frequentist properties even though the statistician making those inferences is unaware that some of the observations were missin...