The Kruskal–Wallis test by ranks or Kruskal–Wallis H test (= one-way ANOVA on ranks) is a non-parametric method for testing whether samples originate from the same distribution (cited after: Kruskal–Wallis H Test using SPSS Statistics, Laerd Statistics).

I agree with Alex Ignatov Also the Chi square test. Don't transform the data; use one of these non parametric tests :)

hello Raja,

Since the data is ordinal, with categories that do not necessarily have equal intervals, it is not appropriate to use a normal ANOVA. Instead, a non-parametric test, such as the Kruskal-Wallis test, can be used to determine if there is a statistically significant difference between the treatments.

The Kruskal-Wallis test is a rank-based test that compares the median scores of each treatment to determine if there is a significant difference between them. To perform this test, follow these steps:

H = 12 / (N(N+1)) * sum(R^2/n) - 3(N+1)

where N is the total number of observations, R is the sum of ranks for each treatment, and n is the number of observations in each treatment.

To determine which treatments are statistically different from each other, post-hoc tests such as Dunn's test or the Wilcoxon-Mann-Whitney test can be used.

It is important to note that since the data is ordinal, the results should be interpreted carefully, and the conclusions should be limited to statements about the median ranks and not the actual values of disease incidence.