title: Missing inaction: the dangers of ignoring missing data.
abstract: The most common approach to dealing with missing data is to delete cases containing missing observations. However, this approach reduces statistical power and increases estimation bias. A recent study shows how estimates of heritability and selection can be biased when the 'invisible fraction' (missing data due to mortality) is ignored, thus demonstrating the dangers of neglecting missing data in ecology and evolution. We highlight recent advances in the procedures of handling missing data and their relevance and applicability.
authors.affiliation: Department of Zoology, University of Otago, PO Box 56, Dunedin 9054, New Zealand. shinichi.nakagawa@otago.ac.nz
authors.forename: Shinichi
authors.initials: S
authors.lastname: Nakagawa
authors.forename: Robert P
authors.initials: RP
authors.lastname: Freckleton
mesh_terms: D005075:Biological Evolution; D004463:Ecology / Q000379:methods / Q000592:standards* / Q000639:trends; D008962:Models, Theoretical; D012107:Research Design / Q000592:standards* / Q000639:trends