In watching the struggle to understand what was meant by the reviewer and to divine how that might accomplished, it seems to me that the reviewer might be wrong and a communication with the editor might be useful.
Gene Maguin
From: SPSSX(r) Discussion <[hidden email]>
On Behalf Of Michael Palij
Sent: Thursday, March 04, 2021 4:09 PM
To: [hidden email]
Subject: Re: how to get overall F-test for GLM ANOVA analysis?
Hi Bruce,
I vaguely remember this argument but since I don't do MANOVA, I am not
invested in using MANOVA as the first stage to determine whether an individual
ANOVA is significant or not. SEM may be more appropriate depending upon
the questions one is asking, the nature of the variables one is using (i.e.,
error free independent variables in traditional experimental designs or
empirical measures of a latent variable such as depression which might
be used as a dependent variable).
The Huberty & Morris argument against using MANOVA prior to individual
ANOVA is somewhat comparable to Rand Wilcox's often stated arguments
that one does need to do an ANOVA if one is going to use standard multiple
comparison procedures (e.g., Tukey's tests, etc.) since these automatically
Control the overall Type I Error Rate/alpha. Only the Fisher's LSD requires
a significant ANOVA before uncorrected t-tests are conducted. If one uses
Bonferroni corrected t-tests, a significant ANOVA is not required either.
In any event, getting back to the OP point of some sort of "general F value",
such a value, at least to me, seems to make sense only in the context of
a two-stage procedure like MANOVA followed by ANOVA or ANOVA followed
by ordinary t-tests.
-Mike Palij
New York University
On Thu, Mar 4, 2021 at 3:05 PM Bruce Weaver <[hidden email]> wrote:
Hi Mike. The classic article (or at least I consider it a classic!) by
Huberty & Morris (1989) explicitly recommends against the practice of
conducting a MANOVA to buy protection against Type I error (a la Fisher's
LSD) and following up with multiple ANOVAs if the MANOVA is statistically
significant. Here are a couple of links for their article:
https://urldefense.proofpoint.com/v2/url?u=https-3A__pdfs.semanticscholar.org_ee6c_77c99c8e4530d0cccaedf85ed525fb22a02d.pdf&d=DwICAg&c=slrrB7dE8n7gBJbeO0g-IQ&r=A8kXUln5f-BYIUaapBvbXA&m=DZEMqc17FKPjMx1EGJmsDt13feNvR7KlDesKBQ3ckq4&s=Ys0wc2RF_1nGZoolPqFfLLFFsGqnM6nd3lvkoQ-cWrA&e=
https://urldefense.proofpoint.com/v2/url?u=https-3A__www.researchgate.net_publication_232494414-5FMultivariate-5FAnalysis-5FVersus-5FMultiple-5FUnivariate-5FAnalyses&d=DwICAg&c=slrrB7dE8n7gBJbeO0g-IQ&r=A8kXUln5f-BYIUaapBvbXA&m=DZEMqc17FKPjMx1EGJmsDt13feNvR7KlDesKBQ3ckq4&s=ctxa4pMHqzKsNmCYPlUleWKPVXw1suwRxOEFp9N_v7Q&e=
And here is the first paragraph of the Discussion section, which summarizes
many of the key points:
--- start of excerpt ---
Even though it is a fairly popular analysis route to take in the behavioral
sciences, conducting a MANOVA as a preliminary step to multiple ANOVAS is
not only unnecessary but irrelevant as well. We consider to be a myth the
idea that one is controlling Type I error probability by following a
significant MANOVA test with multiple ANOVA tests, each conducted using
conventional significance levels. Furthermore, the research questions
addressed by a MANOVA and by multiple ANOVAS are different; the results of
one analysis may have little or no direct substantive bearing on the results
of the other. To require MANOVA as a prerequisite of multiple ANOVAS is
illogical, and the comfort of statistical protection is an illusion. The
view that it is inappropriate to follow a significant MANOVA overall test
with univariate tests is shared by others (e.g., Share, 1984).
--- end of excerpt ---
Cheers,
Bruce
Mike wrote
> A couple of points:
>
> --- snip ---
>
> Assuming a one-way design, one interpretation comes from Fisher's
> protected
> "Least Significant Difference" (LSD) t-test which first requires a
> significant F value
> before one did multiple t-tests (typically at alpha= 0.05 for each test,
> that is, an
> ordinary t-test). If memory serves, obtaining a significant F value
> implies that at
> least one orthogonal contrast will be statistically significant (though
> perhaps not
> the one that one is most interested in). Still, the overall F in this
> situation is still
> evaluated at alpha= 0.05 (If one has a one-way design with a large number
> of
> dependent variables, one could do a MANOVA to determine if there is at
> least
> one difference, following the logic of Fisher's LSD, one could do the
> individual
> ANOVAs at .05 or use a Bonferroni corrected alpha).
-----
--
Bruce Weaver
[hidden email]
https://urldefense.proofpoint.com/v2/url?u=http-3A__sites.google.com_a_lakeheadu.ca_bweaver_&d=DwICAg&c=slrrB7dE8n7gBJbeO0g-IQ&r=A8kXUln5f-BYIUaapBvbXA&m=DZEMqc17FKPjMx1EGJmsDt13feNvR7KlDesKBQ3ckq4&s=d4BKkn3fFgg1FLvxEOOqo4pDW1NPaWrMtjabWspmRbU&e=
"When all else fails, RTFM."
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Sent from: https://urldefense.proofpoint.com/v2/url?u=http-3A__spssx-2Ddiscussion.1045642.n5.nabble.com_&d=DwICAg&c=slrrB7dE8n7gBJbeO0g-IQ&r=A8kXUln5f-BYIUaapBvbXA&m=DZEMqc17FKPjMx1EGJmsDt13feNvR7KlDesKBQ3ckq4&s=r6lpIxyhV3dMuetfkwHO_XJD_gX_el7g-zpmJKEJA9s&e=
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