Statistical analysis of personal radiofrequency electromagnetic field measurements with nondetects

Exposimeters are increasingly applied in bioelectromagnetic research to determine personal radio frequency electromagnetic field (RF-EMF) exposure. The main advantages of exposimeter measurements are their convenient handling for study participants and the large amount Of personal exposure data, which can be obtained for several RF-EMF SOLH-Us. However, the large proportion of measurements below the detection limit is a challenge for data analysis. With the robust ROS (regression oil order statistics) Method, summary statistics can be C calculated by fitting an assumed (distribution to the observed data. We used a preliminary sample of 109 weekly exposimeter measurements from the QUALIFEX study to compare summary statistics computed by robust I OS with a naive approach, where values below the detection limit were replaced by the value Of the detection limit. For the total RF-EMF exposure, differences between the naive approach and the robust ROS were moderate for the 90th percentile and the arithmetic mean. However, exposure contributions from minor RF-EMF sources were considerably overestimated with the naive approach. This results ill an Underestimation Of the exposure range in the population, Which may bias the evaluation of potential exposure-response associations. We conclude from our analyses that summary statistics of exposimeter data calculated by robust ROS are more reliable and more informative than estimates based oil a naive approach. Nevertheless, estimates of source-specific medians or even lower percentiles depend on file assumed data distribution and should be considered With caution.