@misc{10481/102813,
year = {2025},
month = {2},
url = {https://hdl.handle.net/10481/102813},
abstract = {Accurate prevalence estimation is crucial for public health planning, particularly for rare diseases or low-prevalence conditions. This study evaluated frequentist
and Bayesian methods for estimating prevalence, addressing challenges such as imperfect
diagnostic tests, partial disease status verification, and non-probabilistic samples. Poststratification was applied as a novel method and was used to improve representativeness
and correct biases. Three scenarios were analyzed: (1) complete verification using a gold
standard, (2) estimation with a diagnostic test of known sensitivity and specificity, and
(3) partial verification of disease status limited to test positives. In all scenarios, poststratification adjustments increased prevalence estimates and interval lengths, highlighting
the importance of accounting for population variability. Bayesian methods demonstrated
advantages in integrating prior information and modeling uncertainty, particularly under
high-variability and low-prevalence conditions. Key findings included the flexibility of
Bayesian approaches to maintain estimates within plausible ranges and the effectiveness of
post-stratification in correcting biases in non-probabilistic samples. Frequentist methods
provided narrower intervals but were limited in addressing inherent uncertainties. This
study underscores the need for methodological adjustments in epidemiological studies,
offering robust solutions for real-world challenges. These results have significant implications for improving public health decision-making and the design of prevalence studies in
resource-constrained or non-probabilistic contexts.},
publisher = {MDPI},
keywords = {prevalence},
keywords = {diagnostic test},
keywords = {sensitivity},
title = {Point and interval estimation of population prevalence using a fallible test and a non-probabilistic sample: post-stratification correction},
doi = {10.3390/math13050805},
author = {Estrada Alvarez, Jorge Mario and Luna Del Castillo, Juan De Dios and Montero Alonso, Miguel Ángel},
}