Causal assumptions and causal inference in ecological experiments

doi:10.1016/j.tree.2021.08.008

GSTDTAP > 资源环境科学

DOI	10.1016/j.tree.2021.08.008
	Causal assumptions and causal inference in ecological experiments
	Kaitlin Kimmel:Laura E. Dee:Meghan L. Avolio:Paul J. Ferraro
	2021-09-15
发表期刊	Trends in Ecology & Evolution\
出版年	2021
英文摘要	Causal inferences from experimental data are often justified based on treatment randomization. However, inferring causality from data also requires complementary causal assumptions, which have been formalized by scholars of causality but not widely discussed in ecology. While ecologists have recognized challenges to inferring causal relationships in experiments and developed solutions, they lack a general framework to identify and address them. We review four assumptions required to infer causality from experiments and provide design-based and statistically based solutions for when these assumptions are violated.
领域	资源环境
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文献类型	期刊论文
条目标识符	http://119.78.100.173/C666/handle/2XK7JSWQ/338909
专题	资源环境科学
推荐引用方式 GB/T 7714	Kaitlin Kimmel:Laura E. Dee:Meghan L. Avolio:Paul J. Ferraro. Causal assumptions and causal inference in ecological experiments[J]. Trends in Ecology & Evolution\,2021.
APA	Kaitlin Kimmel:Laura E. Dee:Meghan L. Avolio:Paul J. Ferraro.(2021).Causal assumptions and causal inference in ecological experiments.Trends in Ecology & Evolution\.
MLA	Kaitlin Kimmel:Laura E. Dee:Meghan L. Avolio:Paul J. Ferraro."Causal assumptions and causal inference in ecological experiments".Trends in Ecology & Evolution\ (2021).