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TableS7_Case2.R
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TableS7_Case2.R
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#Check values for Table S7
load("ComBat_Scenario3_allcovs_090321.RData")
load("3imgVars_prepostComBat_090221.RData")
load("preComBat_3img3clin_LowerUpper_090121.RData")
#RF: 3 img vars
#LB
median(sensitivityGlio.1.lb)
mad(sensitivityGlio.1.lb)
median(specificityMenin.1.lb)
mad(specificityMenin.1.lb)
median(accuracy.1.lb[,1])
mad(accuracy.1.lb[,1])
#COMBAT.LB: 2a
median(sensitivityGlio.34.lb.post)
mad(sensitivityGlio.34.lb.post)
median(specificityMenin.34.lb.post)
mad(specificityMenin.34.lb.post)
median(accuracy.34.lb.post[,1])
mad(accuracy.34.lb.post[,1])
#quickTest: Case 1a vs. 2a
boxplot(sensitivityGlio.1.lb.post, sensitivityGlio.34.lb.post)
boxplot(specificityMenin.1.lb.post, specificityMenin.34.lb.post)
wilcox.test(specificityMenin.1.lb.post, specificityMenin.34.lb.post,
alternative = "less",
paired = T) #p-val=0.01111
boxplot(accuracy.1.lb.post[,1], accuracy.34.lb.post[,1])
#COMBAT.LB: 2b
median(sensitivityGlio.31.lb.post)
mad(sensitivityGlio.31.lb.post)
median(specificityMenin.31.lb.post)
mad(specificityMenin.31.lb.post)
median(accuracy.31.lb.post[,1])
mad(accuracy.31.lb.post[,1])
#quickTest: Case 1b vs. Case 2b
boxplot(sensitivityGlio.23.lb.post, sensitivityGlio.31.lb.post)
boxplot(specificityMenin.23.lb.post, specificityMenin.31.lb.post)
wilcox.test(specificityMenin.23.lb.post, specificityMenin.31.lb.post,
alternative = "less",
paired = T) #p-val=0.0332
boxplot(accuracy.23.lb.post[,1], accuracy.31.lb.post[,1])
#UB
median(sensitivityGlio.1.ub)
mad(sensitivityGlio.1.ub)
median(specificityMenin.1.ub)
mad(specificityMenin.1.ub)
median(accuracy.1.ub[,1])
mad(accuracy.1.ub[,1])
#RF: 3 img vars + 3 clin covs
#LB
median(sensitivityGlio.2.lb)
mad(sensitivityGlio.2.lb)
median(specificityMenin.2.lb)
mad(specificityMenin.2.lb)
median(accuracy.2.lb[,1])
mad(accuracy.2.lb[,1])
#COMBAT.LB: 2c
median(sensitivityGlio.32.lb.post)
mad(sensitivityGlio.32.lb.post)
median(specificityMenin.32.lb.post)
mad(specificityMenin.32.lb.post)
median(accuracy.32.lb.post[,1])
mad(accuracy.32.lb.post[,1])
range(accuracy.32.lb.post[,1])
#quickTest: Case 1c vs. 2c
boxplot(sensitivityGlio.2.lb.post, sensitivityGlio.32.lb.post)
boxplot(specificityMenin.2.lb.post, specificityMenin.32.lb.post)
wilcox.test(specificityMenin.2.lb.post, specificityMenin.32.lb.post,
alternative = "less",
paired = T) #p-val=0.4016
boxplot(accuracy.2.lb.post[,1], accuracy.32.lb.post[,1])
#COMBAT.LB: 2d
median(sensitivityGlio.33.lb.post)
mad(sensitivityGlio.33.lb.post)
median(specificityMenin.33.lb.post)
mad(specificityMenin.33.lb.post)
median(accuracy.33.lb.post[,1])
mad(accuracy.33.lb.post[,1])
#quickTest: Case 1d vs. 2d
boxplot(sensitivityGlio.22.lb.post, sensitivityGlio.33.lb.post)
boxplot(specificityMenin.22.lb.post, specificityMenin.33.lb.post)
wilcox.test(specificityMenin.22.lb.post, specificityMenin.33.lb.post,
alternative = "less",
paired = T) #p-val=0.003235
boxplot(accuracy.22.lb.post[,1], accuracy.33.lb.post[,1])
#UB
median(sensitivityGlio.2.ub)
mad(sensitivityGlio.2.ub)
median(specificityMenin.2.ub)
mad(specificityMenin.2.ub)
median(accuracy.2.ub[,1])
mad(accuracy.2.ub[,1])
#Check "bold" and "underline" in cells for Table S7
#Lower Bound pre- vs. post-ComBat (bold)
#Lower-Bound post-ComBat vs. Upper Bound (underline)
#2a
#sensitivity
median(sensitivityGlio.1.lb)
median(sensitivityGlio.34.lb.post)
wilcox.test(sensitivityGlio.1.lb, sensitivityGlio.34.lb.post,
alternative = "less",
paired = T) #p-val = 0.1631
median(sensitivityGlio.34.lb.post)
median(sensitivityGlio.1.ub)
wilcox.test(sensitivityGlio.34.lb.post, sensitivityGlio.1.ub,
alternative = "less",
paired = T) #p-val = 0.08892
#specificity
median(specificityMenin.1.lb)
median(specificityMenin.34.lb.post)
wilcox.test(specificityMenin.1.lb, specificityMenin.34.lb.post,
alternative = "less",
paired = T) #p-val = 5.683e-06
median(specificityMenin.34.lb.post)
median(specificityMenin.1.ub)
wilcox.test(specificityMenin.34.lb.post, specificityMenin.1.ub,
alternative = "less",
paired = T) #p-val = 0.2626
#total accuracy
median(accuracy.1.lb[,1])
median(accuracy.34.lb.post[,1])
wilcox.test(accuracy.1.lb[,1], accuracy.34.lb.post[,1],
alternative = "less",
paired = T) #p-val = 6.078e-05
median(accuracy.34.lb.post[,1])
median(accuracy.1.ub[,1])
wilcox.test(accuracy.34.lb.post[,1], accuracy.1.ub[,1],
alternative = "less",
paired = T) #p-val = 0.1488
#2b
#sensitivity
median(sensitivityGlio.1.lb)
median(sensitivityGlio.31.lb.post)
wilcox.test(sensitivityGlio.1.lb, sensitivityGlio.31.lb.post,
alternative = "less",
paired = T) #p-val = 0.5939
median(sensitivityGlio.31.lb.post)
median(sensitivityGlio.1.ub)
wilcox.test(sensitivityGlio.31.lb.post, sensitivityGlio.1.ub,
alternative = "less",
paired = T) #p-val = 0.008529
#specificity
median(specificityMenin.1.lb)
median(specificityMenin.31.lb.post)
wilcox.test(specificityMenin.1.lb, specificityMenin.31.lb.post,
alternative = "less",
paired = T) #p-val = 5.574e-06
median(specificityMenin.31.lb.post)
median(specificityMenin.1.ub)
wilcox.test(specificityMenin.31.lb.post, specificityMenin.1.ub,
alternative = "less",
paired = T) #p-val = 0.08796
#total accuracy
median(accuracy.1.lb[,1])
median(accuracy.31.lb.post[,1])
wilcox.test(accuracy.1.lb[,1], accuracy.31.lb.post[,1],
alternative = "less",
paired = T) #p-val = 0.0001819
median(accuracy.31.lb.post[,1])
median(accuracy.1.ub[,1])
wilcox.test(accuracy.31.lb.post[,1], accuracy.1.ub[,1],
alternative = "less",
paired = T) #p-val = 0.01359
#2c
#sensitivity
median(sensitivityGlio.2.lb)
median(sensitivityGlio.32.lb.post)
wilcox.test(sensitivityGlio.2.lb, sensitivityGlio.32.lb.post,
alternative = "less",
paired = T) #p-val = 1
median(sensitivityGlio.32.lb.post)
median(sensitivityGlio.2.ub)
wilcox.test(sensitivityGlio.32.lb.post, sensitivityGlio.2.ub,
alternative = "less",
paired = T) #p-val = 3.113e-08
#specificity
median(specificityMenin.2.lb)
median(specificityMenin.32.lb.post)
wilcox.test(specificityMenin.2.lb, specificityMenin.32.lb.post,
alternative = "less",
paired = T) #p-val = 1.172e-08
median(specificityMenin.32.lb.post)
median(specificityMenin.2.ub)
wilcox.test(specificityMenin.32.lb.post, specificityMenin.2.ub,
alternative = "less",
paired = T) #p-val = 1
#total accuracy
median(accuracy.2.lb[,1])
median(accuracy.32.lb.post[,1])
wilcox.test(accuracy.2.lb[,1], accuracy.32.lb.post[,1],
alternative = "less",
paired = T) #p-val = 0.4139
median(accuracy.32.lb.post[,1])
median(accuracy.2.ub[,1])
wilcox.test(accuracy.32.lb.post[,1], accuracy.2.ub[,1],
alternative = "less",
paired = T) #p-val = 0.004882
#2d
#sensitivity
median(sensitivityGlio.2.lb)
median(sensitivityGlio.33.lb.post)
wilcox.test(sensitivityGlio.2.lb, sensitivityGlio.33.lb.post,
alternative = "less",
paired = T) #p-val = 1
median(sensitivityGlio.33.lb.post)
median(sensitivityGlio.2.ub)
wilcox.test(sensitivityGlio.33.lb.post, sensitivityGlio.2.ub,
alternative = "less",
paired = T) #p-val = 3.901e-08
#specificity
median(specificityMenin.2.lb)
median(specificityMenin.33.lb.post)
wilcox.test(specificityMenin.2.lb, specificityMenin.33.lb.post,
alternative = "less",
paired = T) #p-val = 3.035e-09
median(specificityMenin.33.lb.post)
median(specificityMenin.2.ub)
wilcox.test(specificityMenin.33.lb.post, specificityMenin.2.ub,
alternative = "less",
paired = T) #p-val = 1
#total accuracy
median(accuracy.2.lb[,1])
median(accuracy.33.lb.post[,1])
wilcox.test(accuracy.2.lb[,1], accuracy.33.lb.post[,1],
alternative = "less",
paired = T) #p-val = 0.2628
median(accuracy.33.lb.post[,1])
median(accuracy.2.ub[,1])
wilcox.test(accuracy.33.lb.post[,1], accuracy.2.ub[,1],
alternative = "less",
paired = T) #p-val = 0.005974