Generating within-person coefficients

[Oliver]

Hi everyone,

I conducted a longitudinal study in which X and Y were measured once a day
for 10 consecutive days. As can be seen attached, my dataset is organized in
a "stacked" way so that I can conduct multilevel analyses.  I was wondering
whether a syntax could be used to generate the "within-person" coefficients
for the association between X and Y ? For instance, for each participant
(ID), I would like to know the magnitude of the association between X and Y.
Is there a way to generate either a correlation coefficient (or any other
statistical estimate quantifying the strength of the X-Y association),
separately for each ID ? I'm not sure if this would be a correlation
coefficient or a beta.

Thanks in advance for your support.
O.

<http://spssx-discussion.1045642.n5.nabble.com/file/t340718/Within-person_estimate.jpg>



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[Andy W]

For exploratory data analysis, you can do something like:

*****************.
SORT CASES BY ID Wave.
SPLIT FILE BY ID.
REGRESSION
  /DEPENDENT y
  /METHOD=ENTER x.
SPLIT FILE OFF.
*****************.

Or swap out CORRELATIONS instead of regression.

For more complicated models (e.g. growth random-effect/fixed-effect), check
out the MIXED command and the SOLUTION option on the RANDOM subcommand
(available as of V25). Or you can do interaction effects with ID and x to
generate person level coefficients.



-----
Andy W
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http://andrewpwheeler.wordpress.com/
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[Rich Ulrich]

Andy suggested the simplest thing to implement.  I've done a couple of other

things, once or twice.

By the way, for the sake of generality, I want to mention that your example

does NOT show any strong trend of linearity across time, which is often an

artifact that confuses interpretations of "time-series" data.  (Hmm, a program

designed for time series might offer desirable options for handling these data.)

You can use Aggregate by ID to collect sums, sums of the squares and cross-products;

and in another step, compute statistics by person from the formulas  for r or b. 

I would also look briefly at whether the variances vary a lot across person, since a

tiny variance for x or y for a person would yield an r or b with a huge error band.

(The number of scores above 90, using a 0-100 range, makes me wonder if you

have a "ceiling effect" which might be deserve some compensatory transformation.

But that wasn't your question.)

Also, for a single Within-Subject correlation matrix across all subjects --

If the number of IDs is not too many, you can use Discriminant Function, where

ID is used as "groups"; that matrix is among the options for output.

--

Rich Ulrich

---

From: SPSSX(r) Discussion <[hidden email]> on behalf of Oliver <[hidden email]>
Sent: Monday, September 23, 2019 8:22 PM
To: [hidden email] <[hidden email]>
Subject: Generating within-person coefficients

 

Hi everyone,

I conducted a longitudinal study in which X and Y were measured once a day
for 10 consecutive days. As can be seen attached, my dataset is organized in
a "stacked" way so that I can conduct multilevel analyses.  I was wondering
whether a syntax could be used to generate the "within-person" coefficients
for the association between X and Y ? For instance, for each participant
(ID), I would like to know the magnitude of the association between X and Y.
Is there a way to generate either a correlation coefficient (or any other
statistical estimate quantifying the strength of the X-Y association),
separately for each ID ? I'm not sure if this would be a correlation
coefficient or a beta.

Thanks in advance for your support.
O.

<http://spssx-discussion.1045642.n5.nabble.com/file/t340718/Within-person_estimate.jpg>



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[Bruce Weaver]

Re Andy's first suggestion, you could use OMS to write the table of
coefficients from the regression model to another dataset for later use.
You'd also have the SEs of the coefficients, which could come in handy if
you wanted to do inverse-variance weighting (for example) to deal with the
issue Rich mentioned about variation in how precisely the slopes are
estimated.  

HTH.


Help for OMS:

https://www.ibm.com/support/knowledgecenter/en/SSLVMB_26.0.0/statistics_reference_project_ddita/spss/base/syn_oms.html




Andy W wrote

> For exploratory data analysis, you can do something like:
>
> *****************.
> SORT CASES BY ID Wave.
> SPLIT FILE BY ID.
> REGRESSION
>   /DEPENDENT y
>   /METHOD=ENTER x.
> SPLIT FILE OFF.
> *****************.
>
> Or swap out CORRELATIONS instead of regression.
>
> For more complicated models (e.g. growth random-effect/fixed-effect),
> check
> out the MIXED command and the SOLUTION option on the RANDOM subcommand
> (available as of V25). Or you can do interaction effects with ID and x to
> generate person level coefficients.
>
>
>
> -----
> Andy W

> apwheele@

> http://andrewpwheeler.wordpress.com/
> --
> Sent from: http://spssx-discussion.1045642.n5.nabble.com/
>
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-----
--
Bruce Weaver
[hidden email]
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"When all else fails, RTFM."

NOTE: My Hotmail account is not monitored regularly.
To send me an e-mail, please use the address shown above.

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[Jon Peck]

If you want to do predictions using results from REGRESSION or many other procedures, the best way is to save the model (Linear > Save > Export model information to XML file) and then use Utilities > Scoring Wizardd to apply it to new data.  That handles things like variable renaming, missing value treatment, and standard errors.

On Tue, Sep 24, 2019 at 12:43 PM Bruce Weaver <[hidden email]> wrote:

Re Andy's first suggestion, you could use OMS to write the table of
coefficients from the regression model to another dataset for later use.
You'd also have the SEs of the coefficients, which could come in handy if
you wanted to do inverse-variance weighting (for example) to deal with the
issue Rich mentioned about variation in how precisely the slopes are
estimated. 

HTH.


Help for OMS:

https://www.ibm.com/support/knowledgecenter/en/SSLVMB_26.0.0/statistics_reference_project_ddita/spss/base/syn_oms.html




Andy W wrote
> For exploratory data analysis, you can do something like:
>
> *****************.
> SORT CASES BY ID Wave.
> SPLIT FILE BY ID.
> REGRESSION
>   /DEPENDENT y
>   /METHOD=ENTER x.
> SPLIT FILE OFF.
> *****************.
>
> Or swap out CORRELATIONS instead of regression.
>
> For more complicated models (e.g. growth random-effect/fixed-effect),
> check
> out the MIXED command and the SOLUTION option on the RANDOM subcommand
> (available as of V25). Or you can do interaction effects with ID and x to
> generate person level coefficients.
>
>
>
> -----
> Andy W

> apwheele@

> http://andrewpwheeler.wordpress.com/
> --
> Sent from: http://spssx-discussion.1045642.n5.nabble.com/
>
> =====================
> To manage your subscription to SPSSX-L, send a message to

> LISTSERV@.UGA

>  (not to SPSSX-L), with no body text except the
> command. To leave the list, send the command
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-----
--
Bruce Weaver
[hidden email]
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 e-mail, please use the address shown above.

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[Oliver]

Hi everyone,

Thanks for getting back to me with suggestions. Everything worked !

Thanks again.
MO.



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