1
$\begingroup$

Say I have two treatments, "hot" and "cold". I care about a certain outcome, say "success". I have data on the number of successes out of, say 100 trials in the "hot" treatment. Similarly, I have data on the number of successes out of 100 trials in the "cold" treatment.

What sort of statistical test should I use to determine whether there is any significant difference between my two treatments with respect to success rate?

$\endgroup$
  • $\begingroup$ Was treatment assignment by randomization or up to the treating physician? Any other factors offer information that may determine outcome or assignment available? $\endgroup$ – Björn Jun 10 '17 at 16:52
  • $\begingroup$ Treatment category was assigned at random. Does that clarify? $\endgroup$ – Atticus29 Jun 10 '17 at 16:56
2
$\begingroup$

This is a basic 2 by 2 frequency table. A chi-square test of independence would be appropriate. Also, you could use a risk ratio or odds ratio to describe the size of the effect and a construct confidence interval around whichever one you choose.

$\endgroup$
1
$\begingroup$

You have two treatments: drug A (hot) and drug B (cold). The Null- Hypothesis would be that cure rate (or proportions) of A equals to the cure rate of B.

Null hypothesis: $p_{A} = p_{B}$

Alternative hypothesis: $p_{A} != p_{B}$

You could use z-test for proportions: $z = \frac{p_{A} - p_{B}}{\sqrt{p(1-p) (\frac{1}{n_A} + \frac{1}{n_B}})}$

And then check the p values.

In python you could use proportions_ztes

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.