Evaluation of a Frequentist Hierarchical Model to Estimate Prevalence when sampling from a large geographic area using Pool Screening.
Evaluation of a Frequentist Hierarchical Model to Estimate Prevalence when sampling from a large geographic area using Pool Screening.
复制标题
使用池筛选从大的地理区域采样时评估频率主义分层模型以估计患病率。
DOI：
10.1080/03610926.2011.633732
复制
发表时间：
2013
期刊：
影响因子：
--
通讯作者：
Katholi,CharlesR
中科院分区：
文献类型：
--
作者：
Birkner,Thomas;Aban,InmaculadaB;Katholi,CharlesR
我们提出了一个频率论的Bernoulli-Beta分层模型，放松了基于合并数据的传统患病率估计方法的恒定患病率假设。当从大的地理区域取样时，这一假设受到质疑。池筛选是一种将单个项目组合到池中的方法。每个样本池将检测为阳性（至少一个项目为阳性）或阴性（所有项目均为阴性）。库筛选通常用于研究热带病，其中库由病媒组成（例如，黑蝇），可以传播疾病。我们的目标是估计的比例感染vector.Intermediate估计（模型参数）和最终利益（有关患病率）的估计进行评估的标准措施的优点，如偏差，方差和均方误差广泛使用的扩展。使用分层模型，研究者可以确定患病率低于预先指定的阈值的概率，该阈值是预期疾病不会再次出现的值。对Beta（α，β）患病率分布中α参数的最小偏倚选择的研究导致选择α = 1。
We present a frequentist Bernoulli-Beta hierarchical model to relax the constant prevalence assumption underlying the traditional prevalence estimation approach based on pooled data. This assumption is called into question when sampling from a large geographic area. Pool screening is a method that combines individual items into pools. Each pool will either test positive (at least one of the items is positive) or negative (all items are negative). Pool screening is commonly applied to the study of tropical diseases where pools consist of vectors (e.g., black flies) that can transmit the disease. The goal is to estimate the proportion of infected vectors.Intermediate estimators (model parameters) and estimators of ultimate interest (pertaining to prevalence) are evaluated by standard measures of merit, such as bias, variance, and mean squared error making extensive use of expansions. Using the hierarchical model an investigator can determine the probability of the prevalence being below a pre-specified threshold value, a value at which no reemergence of the disease is expected. An investigation into the least biased choice of the α parameter in the Beta (α, β) prevalence distribution leads to the choice of α = 1.