The power of statistical tests using field trial count data of non-target organisms in enviromental risk assessment of genetically modified plants

Research output: Contribution to journalArticleAcademicpeer-review

3 Citations (Scopus)

Abstract

Publications on power analyses for field trial count data comparing transgenic and conventional crops have reported widely varying requirements for the replication needed to obtain statistical tests with adequate power. These studies are critically reviewed and complemented with a new simulation study. The reasons for the different reports are elucidated and can be classified as additional (but hidden) replication, selection of favourable endpoints with low variation, and reporting at an unusual scale. A new simulation study was performed to investigate the relationship between statistical power and replication under a variety of data-generating and analysis methods. Approximately 60 replications should be sufficient to detect a 50% (two-fold) decrease in taxon numbers, provided that the coefficient of variation in the counts does not exceed 100%. Replication can be accomplished not only by using multiple blocks in a single trial, but also by repeating the experiment in multiple years and/or at different sites. With other (e.g. agronomic) treatment factors in the field trial, without interaction with variety, the effective replication can be increased by investigating the main variety effect summed over the other treatment factors. Repeated measures may also increase the power if the expected difference is equal over time and the time points are sufficiently spaced.
Original languageEnglish
Pages (from-to)164-172
JournalAgricultural and Forest Entomology
Volume17
DOIs
Publication statusPublished - 2015

Keywords

  • herbicide-tolerant crops
  • farm-scale evaluations
  • varieties
  • design
  • maize
  • taxa
  • corn

Fingerprint Dive into the research topics of 'The power of statistical tests using field trial count data of non-target organisms in enviromental risk assessment of genetically modified plants'. Together they form a unique fingerprint.

  • Cite this