Accuracy of Five Multiple Imputation Methods in Estimating Prevalence of Type 2 Diabetes based on STEPS Surveys
作者: Hamid Heidarian MiriJafar HassanzadehSaeedeh Hajebi KhanikiRahim AkramiEhsan Baradaran Sirjani
刊名: Journal of Epidemiology and Global Health, 2020
来源数据库: Atlantis Press
DOI: 10.2991/jegh.k.191207.001
原始语种摘要: Background: This study was aimed to evaluate five Multiple Imputation (MI) methods in the context of STEP-wise Approach to Surveillance (STEPS) surveys.Methods: We selected a complete subsample of STEPS survey data set and devised an experimental design consisted of 45 states (3 × 3 × 5), which differed by rate of simulated missing data, variable transformation, and MI method. In each state, the process of simulation of missing data and then MI were repeated 50 times. Evaluation was based on Relative Bias (RB) as well as five other measurements that were averaged over 50 repetitions.Results: In estimation of mean, Predictive Mean Matching (PMM) and Multiple Imputation by Chained Equation (MICE) could compensate for the nonresponse bias. Ln and Box–Cox (BC) transformation should be applied...
全文获取路径: Atlantis出版社 

  • could 能够
  • negligible 可忽略的
  • transformation 变换
  • nonresponse 无反应
  • applied 应用的
  • situation 立场
  • missing 失去的
  • estimation 估计
  • respectively 分别
  • satisfactorily 令人满意地