Anthelmintic drug efficacy (ADE) is generally estimated as a population average effect, despite drug responses varying among individuals according to a variety of measurable and non-measurable factors. Model-based and/or individual-level analyses are scarce and often methodologically frail. We propose that wider application of marginal and mixed models would offer benefits to the evaluation of ADE. We demonstrate, with a worked example, how model-based analyses: (i) capture the effects of correlation among hierarchically structured longitudinal data on estimates of ADE; (ii) permit robust inference on the association of measurable factors with ADE; and (iii) enable estimation of variation among individual-level estimates of ADE. The application of modelling approaches is discussed in the context of mass drug administration-based control of human helminthiases.
Keywords: albendazole; hookworm; longitudinal data; marginal models; mass drug administration; mixed models.
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