Giá trị Giới thiệu Censored xảy ra trong dữ liệu môi trường phổ biến nhất là khi mức độ của một hóa chất trong một mẫu vật liệu nhỏ hơn giới hạn định lượng (LOQ), hoặc giới hạn phát hiện (LOD), nơi mà ý nghĩa của LOQ và LOD phụ thuộc vàophương pháp được sử dụng để đo các chất hóa học (Keith, năm 1991, chương 10). Giá trị kiểm duyệt báo cáo là ít hơn so với phát hiện (TNHH), với giới hạn phát hiện (DL) quy định. Có những câu hỏi lớn lên các nhà thống kê cụ. | CHAPTER 10 Censored Data Introduction Censored values occur in environmental data most commonly when the level of a chemical in a sample of material is less than the limit of quantitation LOQ or the limit of detection LOD where the meaning of LOQ and LOD depends on the methods being used to measure the chemical Keith 1991 Chapter 10 . Censored values are generally reported as being less than detectable LTD with the detection limit DL specified. There are questions raised by statisticians in particular about why censoring is done just because a measurement falls below the reporting limit because an uncertain measurement is better than none at all Lambert et al. 1991 . However irrespective of these arguments it does seem that data values are inevitable in the foreseeable future in environmental data sets. Single Sample Estimation Suppose that there is a single random sample of observations some of which are below the detection limit DL. An obvious question then is how to estimate the mean and standard deviation of the population from which the sample was drawn. Some of the approaches that can be used are a With the simple substitution method the censored values are replaced by an assumed value. This might be zero DL DL 2 or a random value from a distribution over the range from zero to DL. After the censored values are replaced the sample is treated as if it were complete to begin with. Obviously replacing censored values by zero leads to a negative bias in estimating the mean while replacing them with DL leads to a positive bias. Using random values from the uniform distribution over the range 0 DL should give about the same estimated mean as is obtained from using DL 2 but gives a better estimate of the population variance Gilliom and Helsel 1986 . 2001 by Chapman Hall CRC b Direct maximum likelihood methods are based on the original work of Cohen 1959 . With these some distribution is assumed for the data and the likelihood function which depends on both
