Optimum allocation of samples in strata-matching case-control studies when cost per sample differs from stratum to...

Area of Science:

• Epidemiology
• Biostatistics
• Statistical modeling

Background:

• Case-control studies are essential in epidemiology for investigating disease causes.
• Efficient sample allocation is crucial for maximizing statistical power and minimizing research costs.
• Existing designs may be suboptimal when sampling costs vary across strata.

Purpose of the Study:

• To determine optimal sample allocation strategies in stratified case-control studies.
• To maximize the efficiency of Cochran's test and minimize variance in odds ratio estimation.
• To provide cost-effective sampling designs for epidemiological research.

Main Methods:

• Derivation of optimal sample allocations under a fixed total cost constraint.
• Analysis of asymptotic efficiency for Cochran's test.
• Evaluation of the maximum likelihood estimator's variance for the common odds ratio.

Main Results:

• The standard design of equal cases and controls per stratum is inefficient when control sampling costs differ significantly.
• Optimal allocation strategies were derived to maximize study efficiency.
• The proposed optimal design demonstrates robustness for commonly encountered odds ratio values in epidemiology.

Conclusions:

• Optimal sample allocation, considering varying stratum costs, is superior to standard equal allocation in case-control studies.
• The derived methods offer improved efficiency and cost-effectiveness for epidemiological research.
• The findings support the adoption of tailored allocation strategies for robust odds ratio estimation.