2011
DOI: 10.1371/journal.pone.0019241
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An Operational Definition of a Statistically Meaningful Trend

Abstract: Linear trend analysis of time series is standard procedure in many scientific disciplines. If the number of data is large, a trend may be statistically significant even if data are scattered far from the trend line. This study introduces and tests a quality criterion for time trends referred to as statistical meaningfulness, which is a stricter quality criterion for trends than high statistical significance. The time series is divided into intervals and interval mean values are calculated. Thereafter, r2 and p… Show more

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Cited by 53 publications
(34 citation statements)
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References 9 publications
(16 reference statements)
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“…The large reduction in significant changes in an incorrectly ordered time series indicates that the findings in the correctly ordered set are of high confidence and likely have a false-positive rate of around 3% to 5%. This false-positive rate is also consistent with the 5% error rate that has been predicted when selecting an r 2 of 0.65 for significant trends in a regression analysis (Bryhn and Dimberg, 2011).…”
Section: Seed Embryo and Endosperm Undergo Hundreds Of Developmentasupporting
confidence: 83%
“…The large reduction in significant changes in an incorrectly ordered time series indicates that the findings in the correctly ordered set are of high confidence and likely have a false-positive rate of around 3% to 5%. This false-positive rate is also consistent with the 5% error rate that has been predicted when selecting an r 2 of 0.65 for significant trends in a regression analysis (Bryhn and Dimberg, 2011).…”
Section: Seed Embryo and Endosperm Undergo Hundreds Of Developmentasupporting
confidence: 83%
“…The method of linear contrasts was used to compare the mean expression of SOX9 in the control with that in the father, the three XY siblings (III1, III3, III5) treated as a group, the two unaffected siblings (III2, III4) treated as a group, and the mother(13, 14). Adjustment was made for the fact that there were replicated observations for each subject.…”
Section: Methodsmentioning
confidence: 99%
“…This study uses statistical tests to compare the observed GST anomaly data record with model-simulated records and detect evidence of warming hiatus periods. Two different statistical methods are used to identify hiatus periods: (1) a type of statistical significance test for data trends-called a "statistical meaningfulness" test [13]-is performed to find periods in model data records with no statistically meaningful GST warming or cooling and (2) large, rapid changes in the GST rate are identified in the model data records which are consistent with variations observed in the recent hiatus.…”
Section: Methodsmentioning
confidence: 99%