http://spssx-discussion.165.s1.nabble.com/Re-example-output-from-crosstabs-column-proportions-tp3422615p3422654.html
Republican Democrat Libertarian Socialist
> Here is another example; this is from my actual dataset, and it's a larger
> than 2x2 table. Variables are Party (4 levels) and Tea Party (2 levels,
> yes or no). I used compare column percentages, with Bonferroni correction.
> And this is what I got. Hope it lines up right.
>
> Am I interpreting this correctly to say that it means Republicans differ
> significantly from Democrats, Libertarians, and Socialists in terms of the
> proportions of them who are members of the Tea Party, and also
> Libertarians differ significantly from Democrats and Socialists, but
> Socialists and Democrats don't differ from each other?
>
>
> Tea Party * Party Crosstabulation
>
> Party
> Republican Democrat Libertarian Socialist
> Tea Party No Count 23a 76b 41c
> 45b
> % within Party 41.8% 100.0% 69.5% 100.0%
>
> Yes Count 32a 0b
> 18c 0b
> % within Party 58.2% .0% 30.5% .0%
>
> Each subscript letter denotes a subset of Party categories whose column
> proportions do not differ significantly from each other at the .05 level.
>
>
>
>
>
>
>
>
>
>> Below is an output from crosstabs using column proportion testing. But
>> what does it show? That 50/50 is significantly different from 20/80?
>> Martin Sherman
>>
>> x * y Crosstabulation
>> y
>> 1.00 2.00 Total
>> x 1.00 Count 40 a 10 b 50
>> % within x 80.0% 20.0% 100.0%
>> % within y 50.0% 20.0% 38.5%
>> 2.00 Count 40 a 40 b 80
>> % within x 50.0% 50.0% 100.0%
>> % within y 50.0% 80.0% 61.5%
>> Total Count 80 50 130
>> % within x 61.5% 38.5% 100.0%
>> % within y 100.0% 100.0% 100.0%
>> Each subscript letter denotes a subset of y categories whose column
>> proportions do not differ significantly from each other at the .05
>> level.
>>
>>
>> -----Original Message-----
>> From: SPSSX(r) Discussion [mailto:
[hidden email]] On Behalf Of
>> Bruce Weaver
>> Sent: Wednesday, March 09, 2011 6:10 PM
>> To:
[hidden email]
>> Subject: Re: chi-square post-hoc tests
>>
>> This is the second or third time I've seen someone mention z-tests under
>> CROSSTABS. I'm not familiar with that--is it new in v19?
>>
>> Thanks,
>> Bruce
>>
>>
>>
>> Bridgette Portman wrote:
>>>
>>> That seems like so much extra work. What about the "compare column
>>> proportions" option under "z-tests" in Crosstabs --> Cells? Is anyone
>>> familiar with using this? If I am interpreting it right, it allows for
>>> the kind of pairwise comparisons I'm trying to do, with the option for
>>> a Bonferroni adjustment to the alpha level.
>>>
>>> Bridgette
>>>
>>>
>>>> If one of the elements remains as 2 levels (e.g., 2 X 3), use
>>>> logistic regression, with the 2-level variable as the outcome. Then
>>>> use appropriate a priori contrasts to disentangle the df (2 df in the
>>>> case of the 3 level variable).
>>>>
>>>> If none of the elements are 2 levels, then you need to consider a
>>>> multinomial logistic regression.
>>>>
>>>> Joe Burleson
>>>>
>>>> -----Original Message-----
>>>> From: SPSSX(r) Discussion [mailto:
[hidden email]] On Behalf
>>>> Of Bridgette Portman
>>>> Sent: Wednesday, March 09, 2011 1:00 AM
>>>> To:
[hidden email]
>>>> Subject: chi-square post-hoc tests
>>>>
>>>> I have another question.
>>>>
>>>> I'm confused about how to perform post-hoc tests for chi-square
>>>> contingency tables larger than 2 x 2. I've been reading up on it in
>>>> books and on the internet, and there seem to be two different methods
>>>> advised.
>>>> Some say to do multiple pairwise comparisons (2x2 tables) with a
>>>> Bonferroni correction. Others say to look at the standardized
>>>> residuals.
>>>> I'm not sure which is the better way. Is there any easy way to
>>>> perform posthoc tests on contingency tables in SPSS?
>>>>
>>>> Thanks,
>>>> Bridgette
>>>>
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>>>
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>>
>>
>> -----
>> --
>> Bruce Weaver
>>
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>>
http://sites.google.com/a/lakeheadu.ca/bweaver/>>
>> "When all else fails, RTFM."
>>
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>> To send me an e-mail, please use the address shown above.
>>
>> --
>> View this message in context:
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