title: Recent temporal trend monitoring of mercury in Arctic biota--how powerful are the existing data sets?
abstract: The goal of this paper is to describe and discuss statistical power with respect to mercury in Arctic biota, using data gathered during the past two or three decades, mostly under the auspices of AMAP Phases I and II. It will describe the current levels of power of existing data sets to detect temporal trends of Hg concentrations. If the desired power is fixed to an appropriate magnitude, the minimum size of a detectable trend within a specified time period or the number of years that is required to detect a certain trend could be estimated provided that the random between-year variation for the current time-series is known. These various measures of performance of the AMAP mercury time-series, derived from the power analysis, are discussed in some detail. The number of years required to detect a certain trend at a particular power at a specific Type I error rate (alpha) is compared with the actual number of years available when the AMAP Phase II assessment was carried out. In general the investigated time-series were too short to possess an acceptable statistical power. The effect of varying the Type-I error rate, the slope of a trend and the desired power is investigated to rank the importance of the various components regulating the statistical power. The consequence of sampling less frequently than once a year is considerable loss of power.
authors.affiliation: Contaminant Research Group, Swedish Museum of Natural History, PO Box 50 007, S-104 05 Stockholm, Sweden.
authors.forename: Anders
authors.initials: A
authors.lastname: Bignert
authors.forename: Frank
authors.initials: F
authors.lastname: Riget
authors.forename: Birgit
authors.initials: B
authors.lastname: Braune
authors.forename: Peter
authors.initials: P
authors.lastname: Outridge
authors.forename: Simon
authors.initials: S
authors.lastname: Wilson
mesh_terms: D000818:Animals; D001110:Arctic Regions; D003627:Data Interpretation, Statistical; D004784:Environmental Monitoring / Q000706:statistics & numerical data; D020387:Food Chain; D008628:Mercury / Q000032:analysis* / Q000493:pharmacokinetics; D015203:Reproducibility of Results; D013997:Time Factors
chemical_list: D008628:Mercury