title: Equivalence versus classical statistical tests in water quality assessments.
abstract: To evaluate whether two unattended field organic carbon instruments could provide data comparable to laboratory-generated data, we needed a practical assessment. Null hypothesis statistical testing (NHST) is commonly utilized for such evaluations in environmental assessments, but researchers in other disciplines have identified weaknesses that may limit NHST's usefulness. For example, in NHST, large sample sizes change p-values and a statistically significant result can be obtained by merely increasing the sample size. In addition, p-values can indicate that observed results are statistically significantly different, but in reality the differences could be trivial in magnitude. Equivalence tests, on the other hand, allow the investigator to incorporate decision criteria that have practical relevance to the study. In this paper, we demonstrate the potential use of equivalence tests as an alternative to NHST. We first compare data between the two field instruments, and then compare the field instruments' data to laboratory-generated data using both NHST and equivalence tests. NHST indicated that the data between the two field instruments and the data between the field instruments and the laboratory were significantly different. Equivalence tests showed that the data were equivalent because they fell within a pre-determined equivalence interval based on our knowledge of laboratory precision. We conclude that equivalence tests provide more useful comparisons and interpretation of water quality data than NHST and should be more widely used in similar environmental assessments.
authors.affiliation: Municipal Water Quality Investigations Program, Division of Environmental Services, California Department of Water Resources, P.O. Box 942836, Sacramento, CA, USA. mngatia@water.ca.gov
authors.forename: Murage
authors.initials: M
authors.lastname: Ngatia
authors.forename: David
authors.initials: D
authors.lastname: Gonzalez
authors.forename: Steve
authors.initials: S
authors.lastname: San Julian
authors.forename: Arin
authors.initials: A
authors.lastname: Conner
mesh_terms: D003627:Data Interpretation, Statistical; D004784:Environmental Monitoring / Q000379:methods* / Q000592:standards; D011786:Quality Control; D015203:Reproducibility of Results; D018401:Sample Size; D014881:Water Supply / Q000032:analysis* / Q000592:standards*