tag:blogger.com,1999:blog-6678912605652689114.post2358089457390748336..comments2017-08-16T04:48:22.369-07:00Comments on SkepStat: Listen to the sound of my voice. You are getting verrry pregggnant....jshttp://www.blogger.com/profile/09076419034887819084noreply@blogger.comBlogger4125tag:blogger.com,1999:blog-6678912605652689114.post-61024252260537486902007-11-23T06:54:00.000-08:002007-11-23T06:54:00.000-08:00Efrique, thanks for your comments. Excellent poin...Efrique, thanks for your comments. Excellent points. Let's see.... <BR/><BR/>I think I really do consider the ignorance of terminology to be highly indicative of general statistical ignorance here. You're absolutely right that not knowing the standard terminology doesn't necessarily imply not knowing how methods work or how to apply them, but I consider it a very bad sign. If someone told me they'd made an astronomical discovery by looking through "the pointy metal apparatus with the lenses," I'd be highly suspicious of their claims. And I just don't consider it in the range of normal variation (if you will) among persons adequately educated in applied statistics to describe a two-sample t-test as an ANOVA in a context such as this paper. (I tried to make this distinction in the post, by describing the use of the term ANOVA for a two-sample test as a "tell," rather than conclusive proof of incompetence, but I may not have been clear enough about the distinction.) <BR/><BR/>You may be right, though, that "profound ignorance" was too strong. Perhaps in a different context, I would have taken it as more of a slip up. There were a number of other aspects of the paper that were "suggestive" of the authors just generally not knowing what they were doing.<BR/><BR/>And thanks especially for the correction about the equivalence between the paired t-test and the special case of two-way ANOVA you describe. Quite right, of course, and what I had written was misleading at best. (I was thinking of one-way ANOVA, as you suggested, but the statement of a lack of equivalence was far too categorical.) I'll edit the post to clear this up.jshttps://www.blogger.com/profile/09076419034887819084noreply@blogger.comtag:blogger.com,1999:blog-6678912605652689114.post-22912642728351850332007-11-23T03:18:00.000-08:002007-11-23T03:18:00.000-08:00I only found your blog today. Interesting! I hope ...I only found your blog today. Interesting! <BR/><BR/>I hope you don't mind if I play a little Devil's Advocate.<BR/><BR/><I>And this is another red flag of profound statistical ignorance: when comparing two paired groups on the mean level of a continuous variable (with an underlying normal distribution), the standard approach is a paired t-test. ANOVA is used to compare more than two groups on the mean of a continuous variable. </I><BR/><BR/>I would not call that "profound ignorance" by any stretch of the imagination. It's perfectly reasonable to regard two sample procedures as special cases of multisample procedures. It may be an usual use of terminology, but that in itself doesn't in any way invalidate the analysis. Ignorance of the usual terminology, at worst, but I wouldn't call it profound.<BR/><BR/><I>And, while it is the case that an ANOVA conducted with two groups instead of more than two groups is mathematically equivalent to a t-test, there is no paired samples version of ANOVA, and thus no equivalence between ANOVA and a paired t-test.</I><BR/><BR/>I guess this will be very upsetting for all those statisticians who have been using ANOVA to analyze randomized block designs all these years. Apparently they've been doing something that doesn't exist.<BR/><BR/>[Sure, it's not <I>one-way</I> ANOVA (obviously), but they definitely call it ANOVA. A paired t-test is equivalent to an ANOVA on a randomized (complete) blocks design with two items per block and two treatments.]<BR/><BR/><I> And no one competent in statistical analysis would describe a two-sample test as an ANOVA anyway, even in the circumstances where that would be technically correct. </I><BR/><BR/>I dispute the assertion in this case. Its perfectly possible to be competent (since that is exactly how I'd describe someone who is technically correct) even if they were unfamiliar with the common use of terminology. Terminology varies from area to area (sometimes to the extent that the same things are reinvented under different names). <BR/><BR/>Again, you might describe them as "ignorant" on that basis, I suppose , since what your describe is pretty standard, but not knowing the common terms isn't, of itself, what makes them incompetent.Efriquehttps://www.blogger.com/profile/08526031804261484547noreply@blogger.comtag:blogger.com,1999:blog-6678912605652689114.post-33795409635768970282007-11-21T17:09:00.000-08:002007-11-21T17:09:00.000-08:00Yes, excellent dissection. It's good to have a pro...Yes, excellent dissection. It's good to have a proper statistician onboard!Damianhttps://www.blogger.com/profile/03045367172566776741noreply@blogger.comtag:blogger.com,1999:blog-6678912605652689114.post-4880513489154900822007-11-21T13:56:00.000-08:002007-11-21T13:56:00.000-08:00Nice analysis of this study. You should submit it ...Nice analysis of this study. You should submit it to a journal or paper to get more people to read it and invalidate this study. It sure looks like someone had something to prove rather than do real science.Anonymousnoreply@blogger.com