Klein Entink, Rinke H. and Fransman, Wouter and Brouwer, Derk H. (2011) How to statistically analyze nano exposure measurement results: using an ARIMA time series approach. Journal of Nanoparticle Research, 13 (12). pp. 6991-7004.
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Measurement strategies for exposure to nano-sized particles differ from traditional integrated sampling methods for exposure assessment by the use of real-time instruments. The resulting measurement series is a time series, where typically the sequential measurements are not independent from each other but show a pattern of autocorrelation. This article addresses the statistical difficulties when analyzing real-time measurements for exposure assessment to manufactured nano objects. To account for autocorrelation patterns, Autoregressive Integrated Moving Average (ARIMA) models are proposed. A simulation study shows the pitfalls of using a standard t-test and the application of ARIMA models is illustrated with three real-data examples. Some practical suggestions for the data analysis of real-time exposure measurements conclude this article.
|Deposited By:||Prof. Alexey Ivanov|
|Deposited On:||05 Jan 2012 09:29|
|Last Modified:||05 Jan 2012 09:42|
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