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Steve Fromm <[log in to unmask]> said:

> There is frequent use of the term "omnibus" (as in "omnibus
> statistic") in the SPM literature.

> Does this term have a precise definition? 

My copy of Chamber's Twentieth Century Dictionary (of the english language) 
includes a definition of "omnibus" as an adjective meaning 'widely 
comprehensive; of miscellaneous contents'. In this case there is an omnibus 
meaning of 'omnibus'!

In SPM it is used in two broad senses:

[1] The first, more classical sense, originates in the Analysis of Variance 
(ANOVA) of a designed experiment, where the F-test for the effect of a factor 
A with more than 2 levels (say k) is often described as an "omnibus" F-test. I 
think the usage of this term can probably be traced back to R A Fisher in the 
1930s.

The reason for this name is that the test includes all the possible contrasts 
and comparisons involving the different levels of the factor A. The numerator 
sum-of-squares of the F statistic is the total of the sums-of-squares for any 
complete set of (k-1) orthogonal contrasts between the k levels of A.

More generally the term 'omnibus F test' gets applied to any situation where 
the numerator degrees of freedom of the F statistic are greater than 1 (e.g. 
effects of interest including conditions and covariates).

Here is an example from [log in to unmask] where it is used in this sense:

(From http://www.mailbase.ac.uk/lists/spm/1998-07/0118.html )

| I'm not sure about the meaning of the SPMF map page after the Design 
| Matrix prompting in SPM Statistic. Does it represent the result of the 
| test of significance of the equality of variances between pixels or 
| something else? 

It's an "extra-sum-of-squares" F-test, assessing the additional 
variance accounted for by the effects of interest (condition effects, 
covariates of interest) after accounting for the effects of no interest 
(nuisance covariates, subject block effects, global effects). As such 
it's an omnibus test for all possible contrasts of the effects of 
interest, answering the question "do the effects of interest model 
anything?" - i.e. "is there any evidence of effects of interest". 

(end of example)

The book 'Human Brain Function' (Frakowiak et al. 1997) also uses the word in 
this sense in the phrase 'omnibus hypothesis' (p. 81).

[2] However the term gets used in a broader way in the SPM discussion list and 
in SPM-related publications. Here it can mean 'a statistic/test for a null 
hypothesis of no effect anywhere in the whole brain vs. some effect 
somewhere', by contrast with a more regionally specified null hypothesis.

This is of course the heart of the 'statistical parametric map' philosophy: to 
take the voxel based statistic (F, t, Z, extra sum-of squares, chi-squared or 
whatever) and consider the resulting 'field' (statistical parametric map). 
Typically one of two things is than done. Either [2.1] seeing whether there 
are any voxels for which the height of the field is significant at a level set 
so the probability that there is one or more such voxels is less than a chosen 
alpha (op. cit. p. 89); or [2.2] applying a more globally based appraisal of 
the field (e.g. spatial extent combined with height) (pp. 89-97).

I append three examples from [log in to unmask]:

(Example from http://www.mailbase.ac.uk/lists/spm/1999-07/0118.html)

> I believe that the set-level analysis implemented in SPM96 is similar 
> to, but not the same as, the MSOS [mean sum of squares] test described 
> by Worsley. This appears to be particularly true when k=0. As I am 
> using SPECT data, where f<1, this is the prefered level of k for 
> set-level inferences, if I understand Friston et al. [Neuroimage 4, 
> 223-35, 1996]. 

Yes indeed. The set-level inference (with k = 0) is a nice omnibus test 
that pertains explicitly to the set of suprathreshold clusters (that 
can then be tabulated). The MSOS is an alternative omnibus test that 
was motivated by the detection of diffuse (less regionally-specific 
effects). These effects cannot be described very concisely because 
they are distributed throughout the brain. 

(Example from http://www.mailbase.ac.uk/lists/spm/1999-02/0017.html)

In another study with apriori anatomical hypotheses, I have used SPM 
without correction for multiple comparisons, and used permutations for 
the omnibus test of significance (based on the number of suprathreshold 
clusters). Region of interest tests were then used for localization. And 
all was fine! 

(Example from http://www.mailbase.ac.uk/lists/spm/1999-01/0017.html)

1) Many people reference Bailey et al (1991) in setting a height threshold 
of p < .001, uncorrected, to reduce risk of false positives with an omnibus 
test. Should one assume that this is adequate and that, having rejected 
correction, one should use the SPM96 default extent threshold of p = 0.5? 

Conclusion: 'omnibus' is used by people discussing SPM to mean 'with respect 
to multiple parameters' and/or 'with respect to the whole brain'. This is 
confusing. I suggest it is restricted to the former (classical) meaning as 
used more widely in statistics, and that an alternative term (e.g. 'global') 
is used for the latter sense. Then we can speak unambiguously of 'global tests 
of contrast activation represented in a t-field' and 'global test of the 
effects of interest represented in an omnibus F-field'. Better than an 
'omnibus omnibus test'!

Ian
---
Ian Nimmo-Smith
MRC Cognition and Brain Sciences Unit
15 Chaucer Road
Cambridge CB2 2EF




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