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comparison between groups on nominal variables
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snowdeni...@gmail.com
Aug 3, 2016, 5:40:55 PM8/3/16
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How does one compare groups on nominal or ordinal variables? I want to know if the groups show significant differences in gender and education. How can one do it on SPSS?
Rich Ulrich
Aug 4, 2016, 2:18:47 AM8/4/16
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On Wed, 3 Aug 2016 14:40:51 -0700 (PDT), snowdeni...@gmail.com
wrote:
>How does one compare groups on nominal or ordinal variables? I want to know if the groups show significant differences in gender and education. How can one do it on SPSS?
Google for the UCLA tutorial on using SPSS in data analysis.
The names of SPSS procedures often match the names of the
tests, such as t-test or ANOVA.
--
Rich Ulrich
wrote:
>How does one compare groups on nominal or ordinal variables? I want to know if the groups show significant differences in gender and education. How can one do it on SPSS?
The names of SPSS procedures often match the names of the
tests, such as t-test or ANOVA.
--
Rich Ulrich
snowdeni...@gmail.com
Aug 4, 2016, 4:28:20 AM8/4/16
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Rich Ulrich
Aug 4, 2016, 12:37:15 PM8/4/16
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On Thu, 4 Aug 2016 01:28:17 -0700 (PDT), snowdeni...@gmail.com
wrote:
Okay. The procedures often match the names of tests. On the
other hand, there are a lot of occasions where you might
apply an F-statistic or a chi-squared, or "goodness-of-fit",
and you need an orientation to know which test meets your
circumstances.
If you can't take a course, at least read the tutorial.
It sounds to me like you wanted a "contingency table" for two
variables but you called upon the "goodness-of-fit" that looked at
each variable alone to see if its cells were all equal. You can get
surer advice if you show the actual syntax that you ran. (A good
practice for everyone is to "paste syntax" from the click-and-choose
interface; save your runs for study (at first) and documentation.
--
Rich Ulrich
wrote:
other hand, there are a lot of occasions where you might
apply an F-statistic or a chi-squared, or "goodness-of-fit",
and you need an orientation to know which test meets your
circumstances.
If you can't take a course, at least read the tutorial.
It sounds to me like you wanted a "contingency table" for two
variables but you called upon the "goodness-of-fit" that looked at
each variable alone to see if its cells were all equal. You can get
surer advice if you show the actual syntax that you ran. (A good
practice for everyone is to "paste syntax" from the click-and-choose
interface; save your runs for study (at first) and documentation.
--
Rich Ulrich
snowdeni...@gmail.com
Aug 4, 2016, 6:33:18 PM8/4/16
to
I do not know how to provide the syntax. So I can just try to give you more information if that is helpful. Basically I want to see if the three groups I have differ in gender since I want them to be similar is some variables such as gender, SES, etc. Thus, all I want to verify is if there are differences between these groups for those variables. I treated SES as an ordinal variable as there is an intrinsic order between the different levels. However, I am struggling to find the best way of conducting the differences between gender. I think the most suitable test would be the chi-squared test of independence, but I am not 100% certain.
Rich Ulrich
Aug 5, 2016, 2:47:31 AM8/5/16
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On Thu, 4 Aug 2016 15:33:16 -0700 (PDT), snowdeni...@gmail.com
If you are happy with reporting the average score for
SES, then SES can be treated as a continuous variable
in an ANOVA. That is fairly conventional.
The usual test for a dichotomy like sex would be the
contingency table. The test will be almost the same
p-value as looking at "average sex" in an ANOVA.
--
Rich Ulrich
SES, then SES can be treated as a continuous variable
in an ANOVA. That is fairly conventional.
The usual test for a dichotomy like sex would be the
contingency table. The test will be almost the same
p-value as looking at "average sex" in an ANOVA.
--
Rich Ulrich
Message has been deleted
snowdeni...@gmail.com
Aug 6, 2016, 1:12:54 AM8/6/16
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Rich Ulrich
Aug 6, 2016, 3:05:11 AM8/6/16
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On Fri, 5 Aug 2016 22:12:52 -0700 (PDT), snowdeni...@gmail.com
wrote:
me>
if one source did not satisfy me, I could dig out ANOTHER one.
Sometimes it is not a matter of being "better", but of being more
compatible with what you, personally, already know or assume.
It might be time to go to a library and browse a few textbooks
used to teach statistics in your field, if you can't find enough
on-line.
--
Rich Ulrich
wrote:
me>
>> If you are happy with reporting the average score for
>> SES, then SES can be treated as a continuous variable
>> in an ANOVA. That is fairly conventional.
>>
>> The usual test for a dichotomy like sex would be the
>> contingency table. The test will be almost the same
>> p-value as looking at "average sex" in an ANOVA.
>>
>
>
>> SES, then SES can be treated as a continuous variable
>> in an ANOVA. That is fairly conventional.
>>
>> The usual test for a dichotomy like sex would be the
>> contingency table. The test will be almost the same
>> p-value as looking at "average sex" in an ANOVA.
>>
>
>
>I did "crosstabs" and chose pearson's chi-square and Phi and Cramer's V on statistics. However, I am still struggling when seeing videos of people using this test for relationship between variables when I want to use it for differences between groups.
About the time I finished my formal education, I figured out that
if one source did not satisfy me, I could dig out ANOTHER one.
Sometimes it is not a matter of being "better", but of being more
compatible with what you, personally, already know or assume.
It might be time to go to a library and browse a few textbooks
used to teach statistics in your field, if you can't find enough
on-line.
--
Rich Ulrich
David Marso
Aug 11, 2016, 4:22:11 PM8/11/16
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Well,if there is a relationship does that not imply that there is a DIFFERENCE? Think about it!
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