Hello, everyone
I want to discuss with you about Hypothesis Testing.
Briefly speaking,
about 350 thousand people have bad liver(bad AST, ALT) so they got medical test for Hepatitis C
and only 38 people among them really have virus of Hepatitis C
and other 850 thousand people didn't get a medical test for Hepatitis C because they have normal AST, ALT
(So they don't know if they are patients or not for Hepatitis C)
In this case, we want to do test between two groups
group C : All people who have virus of Hepatitis C
group D : All people who don't have virus of Hepatitis C
We want to test if there is a significant difference between the mean of BMI of group C and the mean of BMI of group D.
(Also we want to test similarly if there is a significant difference between the mean of weights of group C and the mean of weights of group D
and so on)
Two serious things in this situation are
We don't know, for some of them, if they belong to group C or group D.
And, there is extreme imbalance between the number of group C and the number of group D (group C is too small)
In this case, I want to discuss with you
What is the best strategy or test for this situation
Thank all of you
Do a two sample t test of the difference in means between the tested negative and tested positive groups only.
Because they are of very unequal size they will not satisfy the equal variance condition and you have a Fisher-Behrens problem for which there are several approaches including the Welch test and the Behrens test.
Dear Dr. Leigh:
Thank you so much for your valuable advise.
I understand your point.
And may I ask further:
does it really look impossible to test for whole population?
I have, in fact, several explanatory variables like AST, ALT, Cr, BUN, height, weight, age etc.
However, I found there looks no special interesting variables which may have causal relation with the label (target), which is whether he is positive or negative in Hepatitis C.
Even AST and ALT are not found to have strong relation with the target variable.
Best regards,
Kyoungmun Chang
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