Abstract
Primary results from the Farm Scale Evaluations (FSEs) of spring-sown genetically modified herbicide-tolerant crops were published in 2003. We provide a statistical assessment of the results for count data, addressing issues of sample size (n), efficiency, power, statistical significance, variability and model selection. Treatment effects were consistent between rare and abundant species. Coefficients of variation averaged 73% but varied widely. High variability in vegetation indicators was usually offset by large n and treatment effects, whilst invertebrate indicators often had smaller n and lower variability; overall, achieved power was broadly consistent across indicators. Inferences about treatment effects were robust to model misspecification, justifying the statistical model adopted. As expected, increases in n would improve detectability of effects whilst, for example, halving n would have resulted in a loss of significant results of about the same order. 40% of the 531 published analyses had greater than 80% power to detect a 1.5-fold effect; reducing n by one-third would most likely halve the number of analyses meeting this criterion. Overall, the data collected vindicated the initial statistical power analysis and the planned replication. The FSEs provide a valuable database of variability and estimates of power under various sample size scenarios to aid planning of more efficient future studies.
Abstract from the paper’s OpenAlex record, shown for indexing and research. Copyright remains with the authors or the publisher. Read at the source ↗
The text the model read, with the source record’s inline markup (italics, sub- and superscripts) rendered and its character entities decoded; quote offsets refer to the raw text.
Claims 12
Claim · model-written summary
Treatment effects of the herbicide-tolerant crop regimes were consistent between rare and abundant species.
Verbatim
e1“Treatment effects were consistent between rare and abundant species”
t0“spring-sown genetically modified herbicide-tolerant crops”
Claim · model-written summary
Coefficients of variation of the count data averaged 73% but varied widely.
Verbatim
e2“Coefficients of variation averaged 73% but varied widely”
t0“spring-sown genetically modified herbicide-tolerant crops”
Claim · model-written summary
High variability in vegetation indicators was usually offset by large sample size and treatment effects.
Verbatim
e3“High variability in vegetation indicators was usually offset by large n and treatment effects”
t0“spring-sown genetically modified herbicide-tolerant crops”
Claim · model-written summary
Invertebrate indicators often had smaller sample sizes and lower variability.
Verbatim
e4“invertebrate indicators often had smaller n and lower variability”
t0“spring-sown genetically modified herbicide-tolerant crops”
Claim · model-written summary
Achieved power was broadly consistent across indicators.
Verbatim
e5“overall, achieved power was broadly consistent across indicators”
t0“spring-sown genetically modified herbicide-tolerant crops”
Claim · model-written summary
Inferences about treatment effects were robust to model misspecification.
Verbatim
e6“Inferences about treatment effects were robust to model misspecification”
t0“spring-sown genetically modified herbicide-tolerant crops”
Claim · model-written summary
Increasing sample size would improve the detectability of effects.
Verbatim
e7“increases in n would improve detectability of effects”
t0“spring-sown genetically modified herbicide-tolerant crops”
Claim · model-written summary
Halving sample size would have resulted in a loss of significant results of about the same order.
Verbatim
e0“halving n would have resulted in a loss of significant results of about the same order”
t0“spring-sown genetically modified herbicide-tolerant crops”
Claim · model-written summary
40% of the 531 published analyses had greater than 80% power to detect a 1.5-fold effect.
Verbatim
e0“40% of the 531 published analyses had greater than 80% power to detect a 1.5-fold effect”
t0“spring-sown genetically modified herbicide-tolerant crops”
Claim · model-written summary
Reducing sample size by one-third would most likely halve the number of analyses with adequate power.
Verbatim
e0“reducing n by one-third would most likely halve the number of analyses meeting this criterion”
t0“spring-sown genetically modified herbicide-tolerant crops”
Claim · model-written summary
The data collected vindicated the initial statistical power analysis and the planned replication.
Verbatim
e0“Overall, the data collected vindicated the initial statistical power analysis and the planned replication”
t0“spring-sown genetically modified herbicide-tolerant crops”
Claim · model-written summary
The farm-scale evaluation data form a valuable database of variability and power estimates for planning future studies.
Verbatim
e0“The FSEs provide a valuable database of variability and estimates of power under various sample size scenarios to aid planning of more efficient future studies”
t0“spring-sown genetically modified herbicide-tolerant crops”