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Parameters used in simulation scenarios for the meta-analys..:
Evan M. Adams (6704657)
;
Julia Gulka (11587266)
;
Kathryn A. Williams (11719276)
https://figshare.com/articles/dataset/Parameters_used_in_simulation_scenarios_for_the_meta-analysis_power_analysis_/17034472. , 2021
Link:
https://doi.org/10.1371/journal.pone.0256382.t002
RT Journal T1
Parameters used in simulation scenarios for the meta-analysis power analysis
UL https://suche.suub.uni-bremen.de/peid=base-ftsmithonian:oai:figshare.com:article_17034472&Exemplar=1&LAN=DE A1 Evan M. Adams (6704657) A1 Julia Gulka (11587266) A1 Kathryn A. Williams (11719276) YR 2021 K1 Cancer K1 Science Policy K1 Biological Sciences not elsewhere classified K1 overall sample size K1 found strong evidence K1 compared using aic K1 reduce bat mortality K1 operational minimization tactic K1 likely without accounting K1 effectively reduce fatalities K1 differing curtailment regimes K1 terrestrial wind farms K1 div >< p K1 different treatment categories K1 explore possible linear K1 reducing bat fatalities K1 lower wind speeds K1 low wind conditions K1 turbine curtailment experiments K1 designed curtailment studies K1 detect fatality reductions K1 power analyses showed K1 linear model represented K1 wind farms K1 operational curtailment K1 fatality reductions K1 bat fatality K1 linear model K1 likely due K1 detect effects K1 bat activity K1 linear relationships K1 turbine operations K1 model simplicity K1 united states K1 turbine cut K1 treatment studies K1 substantial support K1 specific studies K1 smaller increases K1 response ratio K1 possible non K1 g K1 examined data K1 easily detectable K1 curtailment cut K1 current dataset K1 continuous variable K1 categorical variable K1 best fit JF https://figshare.com/articles/dataset/Parameters_used_in_simulation_scenarios_for_the_meta-analysis_power_analysis_/17034472 LK http://dx.doi.org/https://doi.org/10.1371/journal.pone.0256382.t002 DO https://doi.org/10.1371/journal.pone.0256382.t002 SF ELIB - SuUB Bremen
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