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Table 8 P values of each variable in the different models.

From: Genetic algorithm with logistic regression for prediction of progression to Alzheimer's disease

Conversion from HC to MCI/AD Conversion from MCI to AD
Variables Pvalues_m1G Pvalues_m1S Pvalues_m2G Pvalues _m2S Variables Pvalues _m3G Pvalues _m3S Pvalues _m4G Pvalues _m4S
V1 0.07   0.002   V1    0.170  
V3 <0.001 <0.001 <0.001 <0.001 V10 0.011 0.019 0.056 0.011
V5 0.003 <0.001 0.014 <0.001 V15    0.048  
V7    0.004   V16   0.046   0.117
V8   0.01 0.251 0.012 V18     0.245
V9     0.021 V19 0.009 0.006 0.008 0.026
V13    0.139   V24 0.043   0.034 0.124
V16    0.109 0.087 V27   0.284   0.233
V17    0.004 0.020 V28     0.092
V18 0.007 0.003 0.001 0.004 V31 0.142   0.154  
V25     0.828 V32    0.549  
V33     0.063 V35 0.104 0.014 0.181 0.033
  1. The results provide statistical support for our finding that variables 3, 5 and 18 dominate prediction of progression of HC to MCI/AD. The prediction of progression from MCI to AD consistently showed the importance of variable 19, and also of variables 10 and 35. These results indicate that for conversion of MCI to AD, the combinations of variables are more important than the contribution of individual variables.