Name
Title | ||
|---|---|---|
Multiple correspondence analysis in predictive logistic modelling: application to a living-donor kidney transplantation data. |
Abstract | ||
|---|---|---|
This work deals with the use of multiple correspondence analysis (MCA) and a weighted Euclidean distance (the tolerance distance) as an exploratory tool in developing predictive logistic models. The method was applied to a living-donor kidney transplant data set with 109 cases and 13 predictors. This approach, followed by backward and forward selection procedures, yielded two models, one with four and another with two predictors. These models were compared to two other models, ordinarily built by backward and forward stepwise selection, which yielded, respectively, five and two predictors. After internal validation, the models performance statistics showed similar results. Likelihood ratio tests suggested that backward approach achieved a better fit than the forward modelling in both methods and the Vuong's non-nested test between backward-built models suggested that these were undistinguishable. We conclude that the tolerance distance, in combination with MCA, could be a feasible method for variable selection in logistic modelling, when there are several categorical predictors. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1016/j.cmpb.2009.02.003 | Computer Methods and Programs in Biomedicine |
Keywords | Field | DocType |
backward-built model,logistic modelling,predictive logistic modelling,living-donor kidney transplantation data,predictive logistic model,forward selection procedure,tolerance distance,models performance statistic,feasible method,weighted euclidean distance,stepwise selection,variable selection,multiple correspondence analysis,so,logistic model,hla,likelihood ratio test,receiver operating characteristic,cn,probability distribution function,statistical modelling,auroc,dna,2d,euclidean distance,singular value decomposition,human leukocyte antigens,rna,da,likelihood ratio,rf,hp,correspondence analysis,svd | Multiple correspondence analysis,Stepwise regression,Likelihood-ratio test,Feature selection,Categorical variable,Computer science,Euclidean distance,Statistical model,Statistics,Correspondence analysis | Journal |
Volume | Issue | ISSN |
95 | 2 | 1872-7565 |
Citations | PageRank | References |
1 | 0.43 | 2 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Renan Moritz Varnier R. Almeida | 1 | 24 | 3.72 |
| Antonio Fernando C. Infantosi | 2 | 60 | 7.71 |
| José Hermógenes R Suassuna | 3 | 2 | 0.95 |
| João Carlos G D Costa | 4 | 2 | 0.95 |