Date: Wed, 19 Jan 2011 17:33:48 0500
ReplyTo: R B <ryan.andrew.black@gmail.com>
Sender: "SPSSX(r) Discussion" <SPSSXL@LISTSERV.UGA.EDU>
From: R B <ryan.andrew.black@gmail.com>
Subject: Re: Bonferroni correction and number of comparisons
InReplyTo: <12954736457313348646.post@n5.nabble.com>
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Bruce,
See a couple of comments interspersed below.
On Wed, Jan 19, 2011 at 4:47 PM, Bruce Weaver <bruce.weaver@hotmail.com> wrote:
> Ryan, multiplying the observed (uncorrected) pvalues by the number of
> contrasts can give you results that make no sense. E.g., if the uncorrected
> pvalue = .25 and the number of contrasts is 6, you'll get a corrected
> pvalue = 1.5. But pvalues are conditional probabilities, and must fall
> within the range 01.
This is a valid point, but I've yet to encounter a situation in my
work where I would've made a different conclusion by correcting alpha
directly.
>
> Here's an example using oneway ANOVA. Notice that the Bonferronicorrected
> pvalues (or Sig. values as SPSS labels them) are not simply 3 x the
> uncorrected (LSD) pvalues.
I disagree. In your example, Bonferroni corrected p values associated
with 1v2 and 1v3 are exactly the same uncorrected pvalues times 3. Is
there something I'm missing here?
My guess is that SPSS automatically replaced the Bonferroni corrected
pvalue associated with 2v3 with 1.0, since as you pointed out the
conditional probability cannot be above 1.0.
>
> MATRIX DATA VARIABLES=Group ROWTYPE_ Score /FACTORS=Group.
> BEGIN DATA
> 1 N 96
> 2 N 96
> 3 N 96
> 1 MEAN 22.98
> 2 MEAN 25.78
> 3 MEAN 26.56
> 1 STDDEV 8.79
> 2 STDDEV 9.08
> 3 STDDEV 8.50
> END DATA.
>
> ONEWAY Score BY group /
> matrix = in(*) /
> POSTHOC=LSD BONFERRONI ALPHA(0.05)
> .
>
> Jan, given that figuring out how to compute corrected pvalues may be quite
> timeconsuming, I would see if I could persuade the person who asked that
> the usual approach (i.e., comparing p to a corrected alpha level) is
> sufficient.
>
> HTH.
>
>
>
> R B wrote:
>>
>> You asked about applying a Bonferroni correction in post hoc tests>
>> "Is the Bonferroni adjustment for 6 comparisons and the corrected
>> pvalue (.05/6=.008333)"
>>
>> Answer. No. You have presumably adjusted the alpha level, not the
>> pvalues. Multiply the each pvalue by the number of post hoc tests
>> performed (6 in the example you provided). Then compare the adjusted
>> pvalues to the alpha level you set (e.g., .05).
>>
>> Ryan
>>
>> On Wed, Jan 19, 2011 at 1:56 PM, J McClure <mc006@pacbell.net> wrote:
>>> Hi,
>>> I am doing a post hoc analysis comparing column proportions and
>>> adjusting (Bonferroni) for multiple comparisons (CTables, test
>>> statistics option).
>>> I've been asked to provide the corrected pvalue.
>>> I'd like to know if I am correct in reporting the corrected value as
>>> .008.
>>> The row variable has two levels (yes and no) and the column variable has
>>> 4 levels, so I am making 6 comparisons for 'no' and 6 for 'yes'.
>>> n*(n1)/2
>>> The output shows the comparison for the 'no' and for the yes level of
>>> the row variable. Is the Bonferroni adjustment for 6 comparisons and the
>>> corrected pvalue (.05/6=.008333)
>>> Also, I have 19 row variables for which I am running column proportion
>>> comparisons. I think that the comparisons for each of the 19 variables
>>> are considered independent from each other so no further adjustment is
>>> made by SPSS. Is this the way reviewers look at the question?
>>> Thanks for any help,
>>> Jan
>>>
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>
>
> 
> 
> Bruce Weaver
> bweaver@lakeheadu.ca
> http://sites.google.com/a/lakeheadu.ca/bweaver/
>
> "When all else fails, RTFM."
>
> NOTE: My Hotmail account is not monitored regularly.
> To send me an email, please use the address shown above.
>
> 
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