Understanding the impact of covariates on the classification of implementation units for soil-transmitted helminths control: a case study from kenya

HIGHLIGHTS

• What: The authors investigate how the use of remotely sensed can help to improve the predictive inferences on prevalence using MBG The authors focus on how the impact on the classification of areas into distinct class of prevalence. The authors compare the performance of two models: one that does not make use of any covariate; and a second model that uses remotely sensed to assist prevalence prediction. The authors also carry out a simulation study in which the authors compare the performance of the two models in the classifications of areal units with varying sample sizes and . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or Email

  Password

  Remember me

  Lost your password?

  If you don't have an account, you can create one here.