A heuristic index for selecting similar categories in multiple correspondence analysis applied to living donor kidney transplantation
This work introduces a heuristic index (the tolerance distance) to define the closeness of two variable categories in multiple correspondence analysis (MCA). This index is a weighted Euclidean distance where weightings are based on the importance of each MCA axis, and variable categories were considered to be associated when their distances were below the tolerance distance. This approach was applied to a renal transplantation data. The analysed variables were allograft survival and 13 of its putative predictors. A bootstrap-based stability analysis was employed for assessing result reliability. The method identified previously detected associations within the database, such as that between race of donors and recipients, and that between HLA match and Cyclosporine use. A hierarchical clustering algorithm was also applied to the same data, allowing for interpretations similar to those based on MCA. The defined tolerance distance could thus be used as an index of closeness in MCA, hence decreasing the subjectivity of interpreting MCA results.
2d bi-dimensional 3d tri-dimensional b1 b2 b3 b4 blood transfusionsfirst second third and fourth quartiles cn immunosuppression protocolwithout cyclosporine a cya cyclosporine a cy immunosuppression protocolwith cyclosporine a d1 d2 d3 d4 donor agefirst da donor raceafro-descendant df donor genderfemale dm donor gendermale dna donor racenon afro-descendant hd type of dialysishaemodialysis hh hla matchhaplo hi hla matchidentical hla human leukocyte antigens hp hla matchpoor pd type of dialysisperitoneal dialysis r1 r2 r3 r4 receptor agefirst ra receptor raceafro-descendant rf receptor genderfemale rm receptor gendermale rn acute rejectionno rna receptor racenon afro-descendant ry acute rejectionyes so allograft survivalabove 60 months svd singular value decomposition su allograft survivalbelow 60 months t1 t2 t3 t4 dialysis timefirst tn previous transplantno ty previous transplantyes