Bliss Robin Y, Weinberg Janice, Vieira Veronica, Ozonoff Al, Webster Thomas F
Department of Biostatistics, Boston University School of Public Health.
J Biom Biostat. 2010 Sep 12;1(104). doi: 10.4172/2155-6180.1000104.
In spatial epidemiology, when applying Generalized Additive Models (GAMs) with a bivariate locally weighted regression smooth over longitude and latitude, a natural hypothesis is whether location is associated with an outcome. An approximate chi-square test (ACST) is available but has an inflated type I error rate. Permutation tests provide alternatives. This research evaluated powers of ACST and four permutation tests: the conditional (CPT), fixed span (FSPT), fixed multiple span (FMSPT), and unconditional (UPT) permutation tests. For CPT, the span size was determined by minimizing the Akaike Information Criterion (AIC) and was held constant for models applied to permuted datasets. For FSPT, a single span was selected a priori. For FMSPT, GAMs were applied using 3-5 different spans selected a priori and the significance cutoff was reduced to account for multiple testing. For UPT, the span was selected by minimizing the AIC for observed and for permuted datasets. Data with a cluster of increased/decreased risk centered in a study region were simulated. ACST and CPT had high power estimates when applied with reduced significance cutoffs to adjust for inflated type I errors. FSPT power depended on the span size; FMSPT power estimates were slightly lower. Overall, UPT had low power.
在空间流行病学中，当应用广义相加模型（GAMs）并对经度和纬度进行双变量局部加权回归平滑处理时，一个自然的假设是位置是否与某个结果相关。有一种近似卡方检验（ACST）可用，但它的I型错误率被夸大了。置换检验提供了替代方法。本研究评估了ACST和四种置换检验的功效：条件置换检验（CPT）、固定跨度置换检验（FSPT）、固定多跨度置换检验（FMSPT）和无条件置换检验（UPT）。对于CPT，跨度大小通过最小化赤池信息准则（AIC）来确定，并在应用于置换数据集的模型中保持不变。对于FSPT，预先选择一个单一跨度。对于FMSPT，使用预先选择的3至5个不同跨度应用GAMs，并降低显著性临界值以考虑多重检验。对于UPT，通过最小化观测数据集和置换数据集的AIC来选择跨度。模拟了以研究区域为中心存在风险增加/降低聚类的数据。当应用降低的显著性临界值来调整夸大的I型错误时，ACST和CPT具有较高的功效估计值。FSPT的功效取决于跨度大小；FMSPT的功效估计值略低。总体而言，UPT的功效较低。
