I have a dataset about nose surgeries done in several years. Some surgeries were combined, e.g. multiple procedures were done during one surgery. After some surgeries, some complications appeared. My task is to determine if there is a statistically significant difference in the frequency of surgeries between combined and independent surgeries. It is assumed that the combined surgeries should have a higher percentage of complications, yet it has to be prooved.
| | Independent | Combined | |------------------------|-------------|----------| | Without a complication | 31 | 123 | | With a complication | 10 | 65 |
Please note there were complications in 24 % of independent surgeries and 35 % of combined surgeries, which is quite a big difference in my opinion.
I used the Chi-Square test of independence, which is as-far-as-I-know the most typical test for this type of task, yet the result is not statistically significant ($\alpha = 0.05$), I had the same result with the Fisher's Exact test. Is there some other test I can try? I found the usage of t-test in some research papers for similar tasks, yet in my opinion, it is not possible to use it here. Or I am missing something?