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Noise exposure-response relationships are used to estimate the effects of noise on individuals or a\udpopulation. Such relationships may be derived from independent or repeated binary observations,\udand modeled by different statistical methods. Depending on the method by which they were established,\udtheir application in population risk assessment or estimation of individual responses may\udyield different results, i.e., predict “weaker” or “stronger” effects. As far as the present body of literature\udon noise effect studies is concerned, however, the underlying statistical methodology to\udestablish exposure-response relationships has not always been paid sufficient attention. This paper\udgives an overview on two statistical approaches (subject-specific and population-averaged logistic\udregression analysis) to establish noise exposure-response relationships from repeated binary observations,\udand their appropriate applications. The considerations are illustrated with data from three\udnoise effect studies, estimating also the magnitude of differences in results when applying\udexposure-response relationships derived from the two statistical approaches. Depending on the\udunderlying data set and the probability range of the binary variable it covers, the two approaches\udyield similar to very different results. The adequate choice of a specific statistical approach and its\udapplication in subsequent studies, both depending on the research question, are therefore crucial

Noise exposure-response relationships established from repeated binary observations: Modeling approaches and applications