The Influence Of Censored Data On Computing Mean Concentrations Of Water Quality Variables Chemical Oxygen Demand And Phosphate [influência De Dados Censurados No Cálculo Da Concentração Média Das Variáveis De Qualidade Da água Demanda Química De Oxigênio E Fosfato]

One of the most common problems in statistical analysis of data from water quality monitoring programs involves the so-called censored data. This study highlights how the sample mean concentration of chemical oxygen demand and phosphate variables are influenced by the estimation method, sample size and percentage of censored data. The confidence interval was used as a metric for comparison of calculated sample mean concentrations on both simple substitution and maximum likelihood estimator (MLE) methods. The results show that sample mean concentrations calculated by simple substitution method are positioned outside the confidence interval. Otherwise, the MLE method produces acceptable values for sample mean concentration, although the magnitude is constrained by sample size and percentage of censored data. The effectiveness of the method depends on an elastic limit of censoring level and sample size. © 2015, ABES - Associacao Brasileira de Engenharia Sanitaria e Ambiental. All rights resevred.202191198Ahn, H., Estimating the mean and variance of censored phosphorus concentrations in Florida rainfall (1998) Journal of the American Water Resources Association, 34 (3), pp. 583-593Aitchinson, J., Brown, I., (1957) The Lognormal Distribution, , Cambridge: Cambridge University PressGilbert, R.O., (1987) Statistical Methods for Environmental Pollution and Monitoring, 336p. , Nova York: WileyGilliom, R.J., Helsel, D.R., Estimation of distributional parameters for censored trace level water quality data: 1. Estimation techniques (1986) Water Resources Research, 22 (1), pp. 135-146Gleit, A., Estimation for small normal data sets with detection limits (1985) Environmental Science & Technology, 19 (12), pp. 1201-1206Helsel, D.R., (2004) Nondetects and Data Analysis: Statistics for Censored Environmental Data, 250p. , New York: John Wily and SonsHelsel, D.R., Cohn, T.A., Estimation of descriptive statistics for multiply censored water quality data (1988) Water Resources Research, 24 (12), pp. 1997-2004Helsel, D.R., Hirsch, R.M., (2002) Statistical Methods in Water Resources. Techniques of Water Resources Investigations of the United States Geological Survey, , http://water.usgs.gov/pubs/twri/twri4a3/, Livro 4, Capítulo A3. Disponível em:Kuttatharmmakul, S., Massart, D.L., Coomans, D., Smeyersverbek, J., Comparison of methods for the estimation of statistical parameters of censored data (2001) Analytica Chimica Acta, 441 (2), pp. 215-229Nascimento, O.C., (2010) Análise De Qualidade Dos Dados Gerados Pelos Programas De Monitoramento Da Qualidade Das águas Das Bacias hidrográficas Do Rio Cuiabá E Rio Das Garças, , Dissertação (Mestrado em Recursos Hídricos) – Universidade Federal de Mato Grosso, CuiabáNewman, M.C., Dixon, P.M., UNCENSOR: A program to estimate means and standard deviations for data sets with below detection limit observations (1990) American Environmental Laboratory, 4 (90), pp. 26-30She, N., Analyzing censored water quality data using a nonparametric approach (1997) Journal of the American Water Resources Association, 33 (3), pp. 615-624Singh, A., Nocerino, J., Robust estimation of mean and variance using environmental data sets with below detection limits observations (2002) Chemometrics and Intelligent Laboratory Systems, 60 (1-2), pp. 69-86Wendelberger, J., Campbell, K., (1994) Non-Detect Data in Environmental Investigations. In: American Statistical Association Conference, , Toront