Iam doing a project looking at two ways to scan a knee and comparing them against surgery they had prior to the scans however it is only in patients who have had surgery is this a conventient sample ? and what tests can i use. I have to wrie a bit in my dissertation plan ???
I have a provisional ethical acceptance now however Iam having trouble with my sample size. It is a paied design. I have a limited number of patients ie.40 and am finding this hard to justify. Any suggestions ??
How much statistical power and how large an effect size are you looking for? Is the sample of n=40 representative of your study population? How are the samples collected and are you doing any randomization? Sorry for all these questions, but I need to know these information in order to justify any sample size. I actually have many more questions.
Woops! Jin snuck in there while I was editing / away from my computer!
Just so I get your study straight in my head:
40 patients who have had knee surgery
20 will be assigned at random to 1 of 2 different scan methods
you want to do a before-after comparison for each of the two groups of 20
Well, yes, it is a convenience sample, but so are lots of biomedical studies - I challenge anyone to find me a single biomedical study that is a purely random sample of the population...
Anyway, a few questions:
- could you get a sample (20 - 40) of similar aged people who have not had surgery? if so, why? I guess I need to understand your study more.
- what's the problem with n=40? especially with a paired design, any statistical test with n=20 and matched pairs should be a pretty powerful test....
- with the scans - exactly what are you "measuring" or evaluating - i.e., what is your dependent variable?
If you were a statistician, you wouldn't be here, and a lot of other people wouldn't be here, and Jin would never get this site to where he wants it to be
Now I see where the sample size issue comes into play. It looks like you're basically comparing the proportion (percentage) of accurate diagnoses between scan method, and you really need a large sample size for proportions.
If you think that one method will be definitively better than the other, then maybe you will still be able to detect a statistical difference, however, if you think that the two methods will be somewhat close, then there may be a problem with statistical power.
Do you have any idea, approximately, what the accuracy rates may be for the two methods, or what the difference may be?
With n=40, and worst case accuracy is around 50% (i.e., no better than flipping a coin), then the standard error of a proportion will be:
SEp = sqrt(p*q/n)
where p=rate of correct diagnoses
q = rate of incorrect diagnoses = 1-p
n = sample size
so, in this example, SEp = sqrt(.5*.5/40) = .079 or approx 8%
Now for a 95% confidence level, you'll need to multiply this % by 1.96, so that brings it up to .155 or 15.5%
- in order to detect a difference between methods, the difference would need to be at least 15-16%, but this is a "worst case" estimate
If the actual diagnosis accuracy rates are higher, then the 15-16% would drop off a bit.....
what about sensitivity and specificity i think the problem is on one of the papers i have read the expected prevelence was 68% from a past paper without dye had a sensitivity of 86%, specificity of 67%, PPV of 83%, NPV of 71%, with dye sensitivity 90%, specificity 78%, PPV 90%, NPV 78%
there were 104 patients in the other study. just worried with a 68% expected prevelence (n=40) that only leaves around 13 patients who wont have tears ??? I just need to some how write something that will keep the ethics comitee happy using some sort of sample size formula statistical power etc.. any ideas
Got the correct result (i dont believe it iam so stressed i cant even do simple maths now!!!!) If i just want to use a simple comparison of accuracies at 65% and 90% is it possible to set this out in the mathamatical form to get n=39 as i cant achieve this ?? sorry for being such a hassle