-------- Original Message -------- Subject: Re: PCA results interpretation Resent-Date: Tue, 27 Jul 2010 11:35:58 -0400 Resent-From: [email protected] Date: Tue, 27 Jul 2010 17:23:57 +0200 From: Miquel Palmer <[email protected]> Reply-To: [email protected] To: [email protected] I can imagine an scenario where PCA1 is not related with between-group differences: When within-group variability is large and related with an unknown covariable (say, size). In that case, some of the PCAs explaining small variability (of the pooled sample) could have large between-group discriminatory power. Miquel Palmer morphmet escribió:
-------- Original Message -------- Subject: PCA results interpretation Date: Mon, 26 Jul 2010 08:49:01 -0700 From: Murat Maga <[email protected]> To: morphmet <[email protected]> Dear morphometricians, I was reading a paper which compared mid-face shape in the unaffected parents of cleft-lip kids versus the age matched controls. Results (and their interpretation) made me think about how far PCA scores can be (or should be) utilized. They ended up using PC2 and PC15 to define and visualize the difference between groups. I wouldn't expect the variation contributed by the first group to the total variation to be too much, they are almost normal after all. But using PC15 to define these characteristics, could this be a bit of stretch? They only reported the total variation accounted by these two components (14.5%). They said none of the other PC showed evidence of group discrimination. I expect PC15 has a minuscule contribution to this sum. So the question I have, is it fair game to fish for PCAs as long as they provide the discrimination you are looking between your groups. Obviously, results don't have to be statistically significant to be biologically relevant. And it is obviously very important to be able to detect people that look normal, but has higher risk of having kids with cleft. But at what point one would say, "yes, PC15 seems to separate them, but could this be an artifact of my samples, or some random noise"? Another statement made by the authors: "This finding [according to authors PC2 separates unaffected male parents from controls and PC15 does the same for females] was confirmed by results showing that mean PC scores on the second component differed significantly between unaffected fathers and male controls (p=.001)". They have a similar statement for PC15 as well. I haven't heard the term "mean PC scores" before? Are they talking about running an anova on the PCs, by using groups as factors? Thanks, M
