The other way to increase effect size would be to improve experimental control (procedure). That would be consistent with this being basically a pilot study.
On Dec 12, 2014, at 8:02 AM, Christopher Green <chri...@yorku.ca> wrote: > Wow. In an era where repeated failures to replicate “sensational” > psychological effects is all over the news, it is astonishing that any editor > would have accepted this sloppy of argument (whether the can cite articles > from the 1960s and ‘70s that used it as well or not). The solution to high > Type II error rates is decidedly not to raise Type I error rates. The > solution is to raise power by raising the sample size. Although it is true > that the conventional alpha level of .05 is entirely arbitrary, in an era > where thousands of psychological studies are published every year (rather > than the mere dozens that were published annually back when Fisher first > proposed it), the conventional Type I error rate should probably be > tightened, not loosened (and the required sample sizes would have to go up > for all but the largest effects). The article should have been rejected until > the authors could demonstrate the same effect with and increased sample size. > > As the old saying goes, extraordinary claims require extraordinary evidence. > > Chris > ….. > Christopher D Green > Department of Psychology > York University > Toronto, ON M3J 1P3 > Canada > > chri...@yorku.ca > http://www.yorku.ca/christo > ………………………………... > > On Dec 11, 2014, at 2:18 PM, Ken Steele <steel...@appstate.edu> wrote: > >> >> A colleague sent me a link to an article - >> >> https://www.insidehighered.com/news/2014/12/10/study-finds-gender-perception-affects-evaluations >> >> I took a look at the original article and found this curious footnote. >> >> Quoting footnote 4 from the study: >> >> "While we acknowledge that a significance level of .05 is conventional in >> social science and higher education research, we side with Skipper, >> Guenther, and Nass (1967), Labovitz (1968), and Lai (1973) in pointing out >> the arbitrary nature of conventional significance levels. Considering our >> study design, we have used a significance level of .10 for some tests where: >> 1) the results support the hypothesis and we are consequently more willing >> to reject the null hypothesis of no difference; 2) our hypothesis is >> strongly supported theoretically and by empirical results in other studies >> that use lower significance levels; 3) our small n may be obscuring large >> differences; and 4) the gravity of an increased risk of Type I error is >> diminished in light of the benefit of decreasing the risk of a Type II error >> (Labovitz, 1968; Lai, 1973).” Paul Brandon Emeritus Professor of Psychology Minnesota State University, Mankato pkbra...@hickorytech.net --- You are currently subscribed to tips as: arch...@mail-archive.com. To unsubscribe click here: http://fsulist.frostburg.edu/u?id=13090.68da6e6e5325aa33287ff385b70df5d5&n=T&l=tips&o=40843 or send a blank email to leave-40843-13090.68da6e6e5325aa33287ff385b70df...@fsulist.frostburg.edu
