Biomedical subjects
Publications and source records attributed to Dennis R Helsel.
Trends in environmental variables are often investigated within a study region at more than one site. At each site, a trend analysis determines whether a trend has occurred. Yet often also of interest is whether a consistent trend is evident throughout the entire region. This paper adapts the Seasonal Kendall trend test to determine whether a consistent regional trend occurs in environmental variables.
The most commonly used method in environmental chemistry to deal with values below detection limits is to substitute a fraction of the detection limit for each nondetect. Two decades of research has shown that this fabrication of values produces poor estimates of statistics, and commonly obscures patterns and trends in the data. Papers using substitution may conclude that significant differences, correlations, and regression relationships do not exist, when in fact they do. The reverse may also be true. Fortunately, good alternative methods for dealing with nondetects already exist, and are summarized here with references to original sources. Substituting values for nondetects should be used rarely, and should generally be considered unacceptable in scientific research. There are better ways.
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Complications arise when ratios are used to present environmental data because ratios are an unbounded, multiplicative scale that can lead to asymmetrical (skewed) data distributions. Enantiomeric ratios (ERs), historically used in discussions of chiral signatures, often are published as mean ER+/-single-value standard deviation. Application of statistical summaries, such as the widely used sample mean and standard deviation, to skewed ratio data is misleading and often inappropriate. Comparison of statistically summarized ER and enantiomer fraction (EF) data (which are based on a bounded, additive scale) for a range of hypothetical values reveals substantial discrepancies when conversion between ER and EF formats is used. These discrepancies are largest when the ratio data are greater than one and have large variability, because the data are more skewed. In many cases, the use of fractions instead of ratios can help to minimize misrepresentation of environmental data, including chiral data. The use of nonparametric statistical summaries, e.g., median and percentiles, provides a more robust indicator of the typical value and spread for both ER and EF data.