Comparison of Means of Two Log-Normal Distributions when Data is Multiply Censored


  •  Abou El-Makarim A. Aboueissa    

Abstract

When measuring concentration of chemical compounds, we often haveto deal with a situation when the resulting values are found belowthe detection limit of the determination method. In order tostatistically evaluate such data, the newly developed method ofmaximum likelihood considering multiply left-censored samples isapplied. This paper is motivated by the need to have validinference concerning the equality of the means of two log-normaldistributions that are frequently encountered in environmental andexposure data analysis. As a model distribution of measuredenvironmental and/or biomedical data, log-normal distribution isconsidered. Moreover, using the asymptotic properties of maximumlikelihood estimates, concentrations of chemicals can be compared.A test procedure for comparing the means of two independentlog-normal populations in the presence of multiply censored datais also introduced and evaluated. Asymptotic chi-square test isused in the proposed test procedure. Worked example is given illustrating the use of the methodsprovided utilizing a computer program written in the R language. Asimulation study was performed to examine the power and the sizeof the proposed test procedure introduced in this article.


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