Well to be precise, for the iris data, the MANOVA gives a p value of something like 1e-40, which is unreachable by NPMANOVA for a reasonable number of permutations. I have only tested NPMANOVA for 100,000 permutations, giving p < 1e-5, so it is indeed possible that NPMANOVA could be orders of magnitude less powerful than MANOVA in this case.
I would be interested to see your data set. Regards, Oyvind Hammer Natural History Museum University of Oslo [EMAIL PROTECTED] On Sat, 10 Nov 2007, morphmet wrote: > Dear professors, > > Thanks for your prompt reply. However we think there is a little > misunderstanding between your replies. According to Dr. Hammer, the > classical Iris data set from Fisher provides similar results between the > parametric and non-parametric MANOVAS. Dr. Rohlf, on the other hand, > suggests that it is expected to have different p-values (in opposite > directions of "significance") between the parametric and non-parametric > alternatives. > > In any case we agree with the suggestion from Dr. Rohlf about the > requirements for larger data sets in the non-parametric tests. > > Given that p-values are not an absolute point of reference we are also > relying on complementary descriptions of the distance among samples, and > complementary indexes about the robustness of p-values. > > Pablo Menendez > Pablo Jarrin > > Quoting morphmet <[EMAIL PROTECTED]>: > >> As Oyvind mentions, the difference in P-values in the two methods is >> in >> the expected direction. It is difficult to tell whether the magnitude >> of >> difference is 'reasonable' without knowing sample sizes and the >> number >> of landmarks. A nonparametric method requires larger sample sizes. >> In >> the discussions concern was mentioned about the assumption of >> normality. >> MANOVA is based on the assumption of homogeneity of within-group >> covariance matrices. That can be more of a problem that modest >> departures from normality (the central limit theorem works for >> multivariate data too). >> >> In the original question it was mentioned that the data shows >> differences mostly along the PC1 axis. That implies that the >> explanation >> for the differences may be one-dimensional. If not size, then >> temperature, north-south gradient, etc. In such cases a general >> multidimensional method such as MANOVA will have less statistical >> power >> than a method such as multivariate regression on some possible >> explanatory variables. >> >> ------------------------ >> F. James Rohlf, Distinguished Professor >> Ecology & Evolution, Stony Brook University >> www: http://life.bio.sunysb.edu/ee/rohlf >> >> >>> -----Original Message----- >>> From: morphmet [mailto:[EMAIL PROTECTED] >>> Sent: Friday, November 09, 2007 9:35 AM >>> To: morphmet >>> Subject: Re: MANOVA vs npMANOVA >>> >>> Hi, it is interesting that you get so different >>> results between MANOVA and NPMANOVA. Would you >>> mind sending me the data set as saved from PAST >>> for me to look at? (I'm the author of PAST). >>> >>> The standard 'Iris' test data set of Fisher gives >>> quite similar results between MANOVA and NPMANOVA >>> of PAST. In general, the NPMANOVA is expected to >>> be less powerful (have higher p values) than MANOVA, >>> I believe. >>> >>> >>> Oyvind Hammer >>> Natural History Museum >>> University of Oslo >>> >>> >>> On Fri, 9 Nov 2007, morphmet wrote: >>> >>>> Dear colleagues, >>>> >>>> We would like to take advantage of Dr. Slice's comments about >> MANOVA >>> to >>>> assess differences among species or biological groups. There are >> few >>>> multivariate normality tests available, however it is often >> common >>> that >>>> Partial Warps (and therefore Relative Warps) from morphological >>>> structures do not fit normality. Thus, we think this is the >> main >>> reason >>>> why Dr. Slice recommends the non-parametric alternatives for >> MANOVA. >>>> More specifically our problem is that we obtain different >> results >>> when >>>> applying either of both parametric and non-parametric MANOVAS. >>>> We are at the moment assessing the relationships between >>> environmental >>>> variables (remote sensing data) and morphological characters >>> (geometric >>>> morphometrics) in a group of Neotropical bats. Neither of both >> types >>> of >>>> variables fit normality very well. >>>> However, what currently puzzle us is the fact that the MANOVA >>> performed >>>> in SPSS give us significant differences, while the np-MANOVA in >> PAST >>>> gives us non significant differences. The contrast in >> magnitude >>>> between both p-values is extreme. We haven?t yet looked at >>> additional >>>> indexes of overlap, confidence or robustness for p-values. >>>> We will be grateful with any comments or suggestions. >>>> Pablo Menendez >>>> Pablo Jarrin >>>> >>>> >>>> >>>> -- >>>> Replies will be sent to the list. >>>> For more information visit http://www.morphometrics.org >>>> >>>> >>> >>> -- >>> Replies will be sent to the list. >>> For more information visit http://www.morphometrics.org >> >> >> >> >> -- >> Replies will be sent to the list. >> For more information visit http://www.morphometrics.org >> > > > > -- > Replies will be sent to the list. > For more information visit http://www.morphometrics.org > > -- Replies will be sent to the list. For more information visit http://www.morphometrics.org
