Non-parametric randomization-based analysis of covariance method in repeated clinical categorical

Objective: Covariance analysis (ANCOVA) is a method used in biomedical and health research, but when the assumption of normality is not satisfied or the dependent variable is bivariate or on ordinal scale, various procedures are presented in the literature for covariance analysis. If assumptions are not satisfied and parametric methods are used, Type I error increases and the power of the test decreases. To overcome these issues, the researcher needs to look for an alternative approach to the analysis of covariance. For non-parametric ANCOVA, many methods are presented in the literature that can be applied to different types of data. Material and Methods: In our study, by analyzing various non-parametric covariance methods; the analysis of repeated categorical data obtained from the clinic is to be analyzed with the non-parametric randomization-based analysis of covariance (NPANCOVA) method. Results: The application of the method was performed on repeated clinical data obtained from 5 consecutive visits from pediatric patients diagnosed with Crimean-Congo hemorrhagic fever disease in the pediatric health and diseases service. Conclusion: As a result, we can state that the NPANCOVA method can be used in clinical analysis due to its many superior advantages in the analysis of categorically repeated non-parametric data