title: Underappreciated problems of low replication in ecological field studies.
abstract: The cost and difficulty of manipulative field studies makes low statistical power a pervasive issue throughout most ecological subdisciplines. Ecologists are already aware that small sample sizes increase the probability of committing Type II errors. In this article, we address a relatively unknown problem with low power: underpowered studies must overestimate small effect sizes in order to achieve statistical significance. First, we describe how low replication coupled with weak effect sizes leads to Type M errors, or exaggerated effect sizes. We then conduct a meta-analysis to determine the average statistical power and Type M error rate for manipulative field experiments that address important questions related to global change; global warming, biodiversity loss, and drought. Finally, we provide recommendations for avoiding Type M errors and constraining estimates of effect size from underpowered studies.
authors.affiliation: Department of Biology, Graduate Degree Program in Ecology, Colorado State University, Fort Collins, Colorado, 80523, USA.
authors.forename: Nathan P
authors.initials: NP
authors.lastname: Lemoine
authors.affiliation: Department of Biology, Graduate Degree Program in Ecology, Colorado State University, Fort Collins, Colorado, 80523, USA.
authors.forename: Ava
authors.initials: A
authors.lastname: Hoffman
authors.affiliation: Department of Biology, Graduate Degree Program in Ecology, Colorado State University, Fort Collins, Colorado, 80523, USA.
authors.forename: Andrew J
authors.initials: AJ
authors.lastname: Felton
authors.affiliation: Department of Biology, Graduate Degree Program in Ecology, Colorado State University, Fort Collins, Colorado, 80523, USA.
authors.forename: Lauren
authors.initials: L
authors.lastname: Baur
authors.affiliation: Department of Biology, Graduate Degree Program in Ecology, Colorado State University, Fort Collins, Colorado, 80523, USA.
authors.forename: Francis
authors.initials: F
authors.lastname: Chaves
authors.affiliation: Department of Biology, Graduate Degree Program in Ecology, Colorado State University, Fort Collins, Colorado, 80523, USA.
authors.forename: Jesse
authors.initials: J
authors.lastname: Gray
authors.affiliation: Department of Biology, Graduate Degree Program in Ecology, Colorado State University, Fort Collins, Colorado, 80523, USA.
authors.forename: Qiang
authors.initials: Q
authors.lastname: Yu
authors.affiliation: Department of Biology, Graduate Degree Program in Ecology, Colorado State University, Fort Collins, Colorado, 80523, USA.
authors.forename: Melinda D
authors.initials: MD
authors.lastname: Smith
mesh_terms: D044822:Biodiversity; D011336:Probability; D012107:Research Design; D018401:Sample Size
keywords: Bayesian statistics; LASSO regression; Type M error; Type S error; power; priors; ridge regression