Timeline for How do I predict subject mean (w/ error) with repeated measurements in SPSS?
Current License: CC BY-SA 3.0
10 events
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| Sep 6, 2020 at 14:12 | history | edited | kjetil b halvorsen♦ |
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| Jun 6, 2012 at 0:36 | vote | accept | DocBuckets | ||
| May 28, 2012 at 4:08 | vote | accept | DocBuckets | ||
| Jun 6, 2012 at 0:36 | |||||
| May 28, 2012 at 4:08 | answer | added | DocBuckets | timeline score: 2 | |
| May 24, 2012 at 20:31 | comment | added | ttnphns |
Predict read by concentration. Estimate and plot upper and lower confidence bounds around the regression line. Compute the mean read for the unknown concentration sample. Intersect this line with the aforementioned confidence bounds and project the two points of intersection on concentration axis. That will be the bounds for concentration of your sample. In your example data, however, there is the problem of heteroscedasticity (cloud is fan-like shape) and hence the usual OLS confidence interval is inappropriate.
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| May 24, 2012 at 17:12 | comment | added | DocBuckets | Also correct. However, in order to have SPSS predict a value of concentration for my unknown, I need to input my read values as independent. I don't know how to have SPSS use a regression model to go from a measured dependent (read) to an estimated independent (concentration) with with error. | |
| May 24, 2012 at 7:30 | comment | added | ttnphns |
It sounds to me that you use concentration as DV and read values as IV. (Am I correct?) This way you naturally get several varying prediction values for the DV. Whereas your calibration concentration values are true (error free) and should be the IV.
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| May 23, 2012 at 21:26 | comment | added | DocBuckets | Correct. The only variation in them would come from random variation in the measurement itself. I should point out that these data are completely simulated. In reality, the "unknown" sample might have actually been measured from independent collections or something to that effect. Either way, I still want to know the same thing: How does one infer an unknown dependent when both the model-building data and the unknown inputs have uncertainty? Can this be done rigorously at all? in SPSS? | |
| May 23, 2012 at 5:38 | comment | added | ttnphns | I don't feel it is right to call it repeated-measurements. Your 6 READ levels don't seem to differ in some systematic way (e.g. condition). Rather, you just performed 6 assessment attempts instead of 1 - for precision. Right? | |
| May 23, 2012 at 0:34 | history | asked | DocBuckets | CC BY-SA 3.0 |