Recovering incomplete data using Statistical Multiple Imputations (SMI): A case study in environmental chemistry

Mercer, Theresa, Frostick, Lynne and Walmsley, Anthony (2011) Recovering incomplete data using Statistical Multiple Imputations (SMI): A case study in environmental chemistry. Talanta, 85 (5). pp. 2599-2604. ISSN 0039-9140

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This paper presents a statistical technique that can be applied to environmental chemistry data where missing values and limit of detection levels prevent the application of statistics. A working example is taken from an environmental leaching study that was set up to determine if there were significant differences in levels of leached arsenic (As), chromium (Cr) and copper (Cu) between lysimeters containing preservative treated wood waste and those containing untreated wood. Fourteen lysimeters were setup and left in natural conditions for 21 weeks. The resultant leachate was analysed by ICP-OES to determine the As, Cr and Cu concentrations. However, due to the variation inherent in each lysimeter combined with the limits of detection offered by ICP-OES, the collected quantitative data was somewhat incomplete. Initial data analysis was hampered by the number of ‘missing values’ in the data. To recover the dataset, the statistical tool of Statistical Multiple Imputation (SMI) was applied, and the data was re-analysed successfully. It was demonstrated that using SMI did not affect the variance in the data, but facilitated analysis of the complete dataset.

Keywords:Data sets, Environmental chemistry, Environmental data, ICP-OES, Incomplete data, Leachates, Limit of detection, Limits of detection, Missing values, Multiple imputation, Natural conditions, Preservative-treated wood, Quantitative data, Statistical techniques, Statistical tools, Arsenic, Chromium, Data reduction, Leaching, Lysimeters, Soil surveys, Statistical mechanics, Statistics
Subjects:F Physical Sciences > F140 Environmental Chemistry
F Physical Sciences > F850 Environmental Sciences
Divisions:College of Science > School of Geography
ID Code:34052
Deposited On:23 Nov 2018 09:52

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