Abstract
We provide a method for estimating the sample mean of a continuous outcome in a stratified population using a double sampling scheme. The stratified sample mean is a weighted average of stratum specific means. It is assumed that the fallible and true outcome data are related by a simple linear regression model in each stratum. The optimal stratified double sampling plan, i.e., the double sampling plan that minimizes the cost of sampling for fixed variances, or alternatively, minimizes the variance for fixed costs, is found and compared to a standard sampling plan. The design parameters are the total sample size and the number of doubly sampled units in each stratum. We show that the optimal double sampling plan is a function of the between-strata and within-strata cost and variance ratios. The efficiency gains, relative to standard sampling plans, under broad set of conditions, are considerable.
Original language | English |
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Pages (from-to) | 163-173 |
Number of pages | 11 |
Journal | Statistics |
Volume | 36 |
Issue number | 2 |
DOIs | |
State | Published - Jun 2002 |
Keywords
- Double sampling
- Efficiency
- Fallible and true outcomes
- Optimal design
- Stratified sampling
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty