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- W2076942817 abstract "Summary Field monitoring, leaching studies, and experimentation in soil biology are often now being done non‐destructively using fixed installations so that measurements are made repeatedly on the same units. The resulting data for each unit (suction cup, lysimeter, incubation chamber) constitute a time series in which there may be autocorrelation. The usual methods of statistical analysis, such as the analysis of variance, must be modified or replaced by more suitable ones to take account of the possible correlation. This paper describes the split‐plot design of such experiments, shows how to assess the variance–covariance matrix of residuals for uniformity by the Greenhouse–Geisser statistic, and shows how to use this statistic to adjust the degrees of freedom in a formal test of significance. It also describes more recent methods. Ante‐dependence analysis identifies the extent of the temporal correlation in the data and provides approximate significance tests for the treatments. Alternatively, the paper also shows how the traditional analysis of variance may be replaced by a restricted maximum likelihood analysis which gives Wald statistics. The techniques are illustrated with data on CO 2 evolved from soil incubated for 75 days in closed chambers, during which time the gas was measured on 24 occasions to give time series for three replicates of each combination of two soils (limed and unlimed) and three types of ryegrass amendment. An ante‐dependence structure (extending to ninth order) weakened the usual significance test within the subunit stratum. The Wald statistics showed that there was, nevertheless, a strong interaction between the treatments and time." @default.
- W2076942817 created "2016-06-24" @default.
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- W2076942817 date "2002-03-01" @default.
- W2076942817 modified "2023-10-18" @default.
- W2076942817 title "Analysing repeated measurements in soil monitoring and experimentation" @default.
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- W2076942817 doi "https://doi.org/10.1046/j.1365-2389.2002.00408.x" @default.
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