Inter and Total Variability [Power / Sample Size]
Dear all,
I will just reply to this post instead of opening a new one (since one issue I want to talk about is again about variabilities).
I'm wondering whether this is correct or not. Let's say we use the same approach for a 2x2 cross-over design, that is,
log(response) = overall mean + sequence + subject + period + trt effect + error,
then we end up with (assume n1 = n2 = n/2) 2n - (n-1) - (2-1) - (2-1) - (2-1) - 1 = n-3.
But we should have n-2 (don't we?) and hence the approach may not be correct at all...?
Thank you in advance for your thoughts and help on that.
Best regards,
Benjamin
I will just reply to this post instead of opening a new one (since one issue I want to talk about is again about variabilities).
- I read in other posts (here) that one cannot get inter (or intra) variability from the total variability and one should avoid rule of thumbs like CV_intra = 60% of CV_total. I agree (I saw the data from Lansoprazole) - at least when talking about CVs. But what about just taking intra variance to be half of the total variance (when only total variance is given)? This approach seems to be a conservative estimate. Usually intra variance is less than or equal to inter variance. It also makes sense coming from the correlation between two responses on the same subject, which is equal to 1/2 if and only if the within variance equals the between variance. Based on this one can calculate CVs. Or not? (the Lansoprazole example should also fulfill this)
- I'm trying to get the degrees of freedom for the following design: one single group, fixed sequence, uncontrolled with respect to time effects (intra-subject design), say n subjects receive k days treatment A, then another k days they receive treatment A and B. More mathematically
log(response) = overall mean + subject + trt effect + error.
I'm wondering whether this is correct or not. Let's say we use the same approach for a 2x2 cross-over design, that is,
log(response) = overall mean + sequence + subject + period + trt effect + error,
then we end up with (assume n1 = n2 = n/2) 2n - (n-1) - (2-1) - (2-1) - (2-1) - 1 = n-3.
But we should have n-2 (don't we?) and hence the approach may not be correct at all...?
Thank you in advance for your thoughts and help on that.
Best regards,
Benjamin
Complete thread:
- Inter and Total Variability Ben 2011-09-02 13:43 [Power / Sample Size]
- Inter and Total Variability Helmut 2011-09-02 14:21
- Inter and Total Variability Ben 2011-09-03 11:28
- Inter and Total VariabilityBen 2011-09-08 19:22
- Inter and Total Variability Helmut 2011-09-11 11:55
- Inter and Total Variability Ben 2011-09-13 22:03
- Inter and Total Variability Helmut 2011-09-14 00:43
- Inter and Total Variability Ben 2011-09-18 12:36
- Inter and Total Variability Ben 2011-10-06 18:51
- Inter-subject variance sasophylistic (GLM vs. MIXED) d_labes 2011-10-07 13:33
- Inter and Total Variability Helmut 2011-09-14 00:43
- Inter and Total Variability Ben 2011-09-13 22:03
- Inter and Total Variability ElMaestro 2011-09-18 14:14
- Inter and Total Variability Ben 2011-09-19 19:43
- Inter and Total Variability Helmut 2011-09-11 11:55
- Inter and Total VariabilityBen 2011-09-08 19:22
- Inter and Total Variability Ben 2011-09-03 11:28
- Inter and Total Variability Helmut 2011-09-02 14:21