Posted by
Swank, Paul R on
Feb 20, 2013; 4:10am
URL: http://spssx-discussion.165.s1.nabble.com/Longitudinal-comparison-partial-vs-whole-sample-tp5718123p5718139.html
This is fraught with problems. The 20 at time 2 are the same people as those 20 observations at time 1 but different form the 56 people at time 1 who don't have time 2 data. So to just compare the means, you are mixing independent and dependent observations. I figure you have 3 options: 1) compare the 20 at time 2 with the same 20 at time 1 using a repeated measures approach or a paired t test (assuming the distributions are relatively symmetric and unimodal); 2) compare the 20 at time 2 with the 56 at time 1 who didn't have time 2 data using an independent samples test; 3) use a mixed models approach to repeated measures which does not use listwise deletion. At least then, the variance estimates will be less biased than using listwise deletion.
Dr. Paul R. Swank, Professor
Health Promotion and Behavioral Sciences
School of Public Health
University of Texas Health Science Center Houston
-----Original Message-----
From: SPSSX(r) Discussion [mailto:
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Sent: Tuesday, February 19, 2013 4:42 AM
To:
[hidden email]
Subject: Longitudinal comparison partial vs. whole sample
Hello everybody,
I have eye tracking data of a total sample (n = 76) at testing point 1 (T1) and of a partial sample (n = 20) at testing point 2 (T2).
I want to compare the eye tracking performances of the test persons from the partial sample at T2 with those of the total sample at T1.
That means, that the total sample should represent a norm sample and I want to test, whether the T2 partial sample differs from this norm.
Which statistical test do I have to use (bearing in mind the longitudinal
design) and how do I do that in SPSS?
If possible: Do you have any literature references for an approach concerning this "problem".
Best regards,
Sebastian
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