title: On confidence intervals for within-subjects designs.
abstract: Confidence intervals (CIs) for means are frequently advocated as alternatives to null hypothesis significance testing (NHST), for which a common theme in the debate is that conclusions from CIs and NHST should be mutually consistent. The authors examined a class of CIs for which the conclusions are said to be inconsistent with NHST in within-subjects designs and a class for which the conclusions are said to be consistent. The difference between them is a difference in models. In particular, the main issue is that the class for which the conclusions are said to be consistent derives from fixed-effects models with subjects fixed, not mixed models with subjects random. Offered is mixed model methodology that has been popularized in the statistical literature and statistical software procedures. Generalizations to different classes of within-subjects designs are explored, and comments on the future direction of the debate on NHST are offered.
authors.affiliation: Department of Experimental Statistics, Louisiana State University, Baton Rouge, LA 70803, USA. dblouin@lsu.edu
authors.forename: David C
authors.initials: DC
authors.lastname: Blouin
authors.forename: Arthur J
authors.initials: AJ
authors.lastname: Riopelle
mesh_terms: D016001:Confidence Intervals; D003627:Data Interpretation, Statistical; D006801:Humans; D008960:Models, Psychological; D011582:Psychological Theory; D012107:Research Design