options(scipen = 999)
library(epiDisplay)## Loading required package: foreign## Loading required package: survival## Loading required package: MASS## Loading required package: nnetlibrary(rms)## Loading required package: Hmisc## Loading required package: lattice##
## Attaching package: 'lattice'## The following object is masked from 'package:epiDisplay':
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## dotplot## Loading required package: Formula## Loading required package: ggplot2##
## Attaching package: 'ggplot2'## The following object is masked from 'package:epiDisplay':
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## alpha##
## Attaching package: 'Hmisc'## The following objects are masked from 'package:base':
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## format.pval, units## Loading required package: SparseM##
## Attaching package: 'SparseM'## The following object is masked from 'package:base':
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## backsolve## Registered S3 method overwritten by 'rms':
## method from
## print.lrtest epiDisplay##
## Attaching package: 'rms'## The following object is masked from 'package:epiDisplay':
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## lrtestlibrary(BMA)## Loading required package: leaps## Loading required package: robustbase##
## Attaching package: 'robustbase'## The following object is masked from 'package:survival':
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## heart## Loading required package: inline## Loading required package: rrcov## Scalable Robust Estimators with High Breakdown Point (version 1.4-9)library(DescTools)##
## Attaching package: 'DescTools'## The following object is masked from 'package:rrcov':
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## Cov## The following objects are masked from 'package:Hmisc':
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## %nin%, Label, Mean, Quantilet = "C:\\Users\\Admin\\Desktop\\chi Thuy.csv"
thuy = read.csv(t)
attach(thuy)
head(thuy)## doctinh tutha ShockNK giamalbumin tangbilirubin ACEIARB Aminosid Furosemid
## 1 0 1 0 1 0 0 0 1
## 2 0 0 0 1 0 0 0 0
## 3 0 1 1 1 0 0 0 1
## 4 0 0 0 1 0 0 1 1
## 5 1 1 0 1 0 0 1 1
## 6 1 1 1 1 0 0 0 1
## vanmach NSAIDs Vancomycin Teicoplanin Rifampicin gioitinh tuoi Scrbandau THA1
## 1 0 0 0 0 0 1 74 55.5 0
## 2 0 0 1 0 0 1 65 73.1 0
## 3 1 0 0 0 0 1 84 93.1 0
## 4 0 1 0 0 0 1 84 175.4 1
## 5 1 0 0 0 0 1 89 71.9 0
## 6 1 0 0 0 0 1 81 185.7 0
## DTD2 Lieuduytringaydau lieutu9MUI canquang Songaydung lieutichluytong
## 1 0 3 0 0 13 39.0
## 2 0 6 0 0 4 24.0
## 3 0 6 0 0 11 66.0
## 4 0 2 0 0 15 30.5
## 5 0 3 0 0 11 33.0
## 6 0 6 0 0 7 42.0MÔ HÌNH 1: BAO GỒM TẤT CẢ CÁC BIẾN
y = thuy$doctinh
xvars1 = thuy[,c(2:23)]Lựa chọn mô hình
mohinh1 = bic.glm(xvars1, y , strict = F, OR = 20, glm.family = binomial, data = thuy)
summary(mohinh1)##
## Call:
## bic.glm.data.frame(x = xvars1, y = y, glm.family = binomial, strict = F, OR = 20, data = thuy)
##
##
## 66 models were selected
## Best 5 models (cumulative posterior probability = 0.4045 ):
##
## p!=0 EV SD model 1 model 2
## Intercept 100 -5.22352144 1.1831583 -6.20867 -5.73425
## tutha.x 93.7 1.06466734 0.4491483 1.29197 1.18771
## ShockNK.x 0.7 0.00023498 0.0347746 . .
## giamalbumin.x 100.0 1.62336772 0.4547652 1.55729 1.66964
## tangbilirubin.x 3.3 0.01637326 0.1380975 . .
## ACEIARB.x 4.3 0.02178070 0.1397908 . .
## Aminosid.x 96.3 1.27406934 0.4881461 1.42102 1.40688
## Furosemid.x 30.7 0.24669482 0.4234174 . .
## vanmach.x 7.0 0.04044859 0.1848630 . .
## NSAIDs.x 2.6 0.00620525 0.0797976 . .
## Vancomycin.x 5.5 -0.04149910 0.2217482 . .
## Teicoplanin.x 5.0 0.05323039 0.3183902 . .
## Rifampicin.x 1.3 0.00317461 0.1052965 . .
## gioitinh.x 2.8 0.00645322 0.0707598 . .
## tuoi.x 2.0 0.00008294 0.0015625 . .
## Scrbandau.x 0.7 -0.00000164 0.0002072 . .
## THA1.x 2.8 0.00542276 0.0670847 . .
## DTD2.x 35.2 0.32702942 0.5068695 0.99086 .
## Lieuduytringaydau.x 100.0 0.39382785 0.1557536 0.52852 0.48383
## lieutu9MUI.x 3.1 -0.01679383 0.1546654 . .
## canquang.x 1.3 -0.00231936 0.0884571 . .
## Songaydung.x 52.8 0.08757020 0.0947398 0.18499 0.16609
## lieutichluytong.x 49.5 -0.01273833 0.0142517 -0.02708 -0.02492
##
## nVar 7 6
## BIC -1179.73723 -1179.28879
## post prob 0.113 0.090
## model 3 model 4 model 5
## Intercept -4.67818 -4.05247 -4.25122
## tutha.x 0.94025 1.13216 1.20330
## ShockNK.x . . .
## giamalbumin.x 1.65561 1.66467 1.56225
## tangbilirubin.x . . .
## ACEIARB.x . . .
## Aminosid.x 1.19091 1.30291 1.29477
## Furosemid.x 0.81386 . .
## vanmach.x . . .
## NSAIDs.x . . .
## Vancomycin.x . . .
## Teicoplanin.x . . .
## Rifampicin.x . . .
## gioitinh.x . . .
## tuoi.x . . .
## Scrbandau.x . . .
## THA1.x . . .
## DTD2.x . . 0.75359
## Lieuduytringaydau.x 0.29807 0.25982 0.27915
## lieutu9MUI.x . . .
## canquang.x . . .
## Songaydung.x . . .
## lieutichluytong.x . . .
##
## nVar 5 4 5
## BIC -1179.12914 -1179.07987 -1177.46901
## post prob 0.083 0.081 0.036Xây dựng mô hình hồi quy đa biến #Đọc kết quả adj.OR và p (LR test)
m1 = glm(doctinh ~tutha + giamalbumin + Aminosid + DTD2 + Lieuduytringaydau + Songaydung + lieutichluytong , family = binomial, data = thuy)
logistic.display(m1)##
## Logistic regression predicting doctinh
##
## crude OR(95%CI) adj. OR(95%CI)
## tutha: 1 vs 0 3.53 (1.97,6.34) 3.64 (1.84,7.18)
##
## giamalbumin: 1 vs 0 5.83 (2.65,12.82) 4.75 (1.96,11.48)
##
## Aminosid: 1 vs 0 3.27 (1.62,6.62) 4.14 (1.79,9.57)
##
## DTD2: 1 vs 0 1.87 (1,3.53) 2.69 (1.22,5.96)
##
## Lieuduytringaydau (cont. var.) 1.27 (1.11,1.45) 1.7 (1.33,2.16)
##
## Songaydung (cont. var.) 1.05 (1.01,1.09) 1.2 (1.08,1.34)
##
## lieutichluytong (cont. var.) 1.01 (1,1.01) 0.97 (0.96,0.99)
##
## P(Wald's test) P(LR-test)
## tutha: 1 vs 0 < 0.001 < 0.001
##
## giamalbumin: 1 vs 0 < 0.001 < 0.001
##
## Aminosid: 1 vs 0 < 0.001 < 0.001
##
## DTD2: 1 vs 0 0.014 0.014
##
## Lieuduytringaydau (cont. var.) < 0.001 < 0.001
##
## Songaydung (cont. var.) < 0.001 < 0.001
##
## lieutichluytong (cont. var.) 0.002 < 0.001
##
## Log-likelihood = -120.581
## No. of observations = 263
## AIC value = 257.162Đánh giá mô hình hồi quy logistic
#Chỉ số AUC: C (0.823)
#Chỉ số pseudo-R2: R2 (0.361)
f1 = lrm(doctinh ~tutha + giamalbumin + Aminosid + DTD2 + Lieuduytringaydau + Songaydung + lieutichluytong, data = thuy)
f1## Logistic Regression Model
##
## lrm(formula = doctinh ~ tutha + giamalbumin + Aminosid + DTD2 +
## Lieuduytringaydau + Songaydung + lieutichluytong, data = thuy)
##
## Model Likelihood Discrimination Rank Discrim.
## Ratio Test Indexes Indexes
## Obs 263 LR chi2 76.87 R2 0.361 C 0.823
## 0 186 d.f. 7 g 1.770 Dxy 0.645
## 1 77 Pr(> chi2) <0.0001 gr 5.870 gamma 0.646
## max |deriv| 8e-07 gp 0.265 tau-a 0.268
## Brier 0.153
##
## Coef S.E. Wald Z Pr(>|Z|)
## Intercept -6.2087 0.9231 -6.73 <0.0001
## tutha 1.2920 0.3469 3.72 0.0002
## giamalbumin 1.5573 0.4507 3.46 0.0005
## Aminosid 1.4210 0.4274 3.32 0.0009
## DTD2 0.9909 0.4048 2.45 0.0144
## Lieuduytringaydau 0.5285 0.1235 4.28 <0.0001
## Songaydung 0.1850 0.0536 3.45 0.0006
## lieutichluytong -0.0271 0.0086 -3.13 0.0017
## MÔ HÌNH 2: BỎ BIẾN “LIỀU TÍCH LŨY”
xvars2 = thuy[,c(2:22)]
mohinh2 = bic.glm(xvars2, y , strict = F, OR = 20, glm.family = binomial, data = thuy)
summary(mohinh2)##
## Call:
## bic.glm.data.frame(x = xvars2, y = y, glm.family = binomial, strict = F, OR = 20, data = thuy)
##
##
## 49 models were selected
## Best 5 models (cumulative posterior probability = 0.4366 ):
##
## p!=0 EV SD model 1 model 2
## Intercept 100 -4.424404057 0.7496299 -4.6782 -4.0525
## tutha.x 89.5 0.940400473 0.4639185 0.9402 1.1322
## ShockNK.x 1.8 -0.000170457 0.0527365 . .
## giamalbumin.x 100.0 1.641724730 0.4532136 1.6556 1.6647
## tangbilirubin.x 2.5 0.011403897 0.1140149 . .
## ACEIARB.x 3.2 0.015922917 0.1196607 . .
## Aminosid.x 93.8 1.159584251 0.4979707 1.1909 1.3029
## Furosemid.x 52.8 0.446416631 0.4960618 0.8139 .
## vanmach.x 4.9 0.024041630 0.1394339 . .
## NSAIDs.x 2.1 0.004915733 0.0699036 . .
## Vancomycin.x 6.8 -0.055002562 0.2548914 . .
## Teicoplanin.x 6.3 0.079761981 0.3865728 . .
## Rifampicin.x 1.9 0.007669476 0.1304272 . .
## gioitinh.x 2.3 0.006008697 0.0658566 . .
## tuoi.x 2.2 0.000128454 0.0016753 . .
## Scrbandau.x 1.8 -0.000003341 0.0003362 . .
## THA1.x 2.2 0.004584979 0.0573597 . .
## DTD2.x 17.4 0.126711591 0.3193756 . .
## Lieuduytringaydau.x 100.0 0.281772212 0.0842971 0.2981 0.2598
## lieutu9MUI.x 2.4 -0.012462207 0.1317450 . .
## canquang.x 1.8 0.002692843 0.0974426 . .
## Songaydung.x 7.1 0.002183471 0.0098813 . .
##
## nVar 5 4
## BIC -1179.1291 -1179.0799
## post prob 0.144 0.140
## model 3 model 4 model 5
## Intercept -4.2512 -4.5340 -4.8189
## tutha.x 1.2033 . 1.0176
## ShockNK.x . . .
## giamalbumin.x 1.5623 1.8255 1.5703
## tangbilirubin.x . . .
## ACEIARB.x . . .
## Aminosid.x 1.2948 1.1549 1.2018
## Furosemid.x . 1.0309 0.7586
## vanmach.x . . .
## NSAIDs.x . . .
## Vancomycin.x . . .
## Teicoplanin.x . . .
## Rifampicin.x . . .
## gioitinh.x . . .
## tuoi.x . . .
## Scrbandau.x . . .
## THA1.x . . .
## DTD2.x 0.7536 . 0.6779
## Lieuduytringaydau.x 0.2791 0.2775 0.3125
## lieutu9MUI.x . . .
## canquang.x . . .
## Songaydung.x . . .
##
## nVar 5 4 6
## BIC -1177.4690 -1176.9035 -1176.6867
## post prob 0.063 0.047 0.042m2 = glm(doctinh ~tutha + giamalbumin + Aminosid + Furosemid + Lieuduytringaydau , family = binomial, data = thuy)
logistic.display(m2)##
## Logistic regression predicting doctinh
##
## crude OR(95%CI) adj. OR(95%CI)
## tutha: 1 vs 0 3.53 (1.97,6.34) 2.56 (1.32,4.97)
##
## giamalbumin: 1 vs 0 5.83 (2.65,12.82) 5.24 (2.16,12.71)
##
## Aminosid: 1 vs 0 3.27 (1.62,6.62) 3.29 (1.48,7.31)
##
## Furosemid: 1 vs 0 2.78 (1.56,4.96) 2.26 (1.14,4.47)
##
## Lieuduytringaydau (cont. var.) 1.27 (1.11,1.45) 1.35 (1.14,1.59)
##
## P(Wald's test) P(LR-test)
## tutha: 1 vs 0 0.005 0.005
##
## giamalbumin: 1 vs 0 < 0.001 < 0.001
##
## Aminosid: 1 vs 0 0.003 0.003
##
## Furosemid: 1 vs 0 0.02 0.018
##
## Lieuduytringaydau (cont. var.) < 0.001 < 0.001
##
## Log-likelihood = -126.4572
## No. of observations = 263
## AIC value = 264.9144f2 = lrm(doctinh ~tutha + giamalbumin + Aminosid + Furosemid + Lieuduytringaydau, data = thuy)
f2## Logistic Regression Model
##
## lrm(formula = doctinh ~ tutha + giamalbumin + Aminosid + Furosemid +
## Lieuduytringaydau, data = thuy)
##
## Model Likelihood Discrimination Rank Discrim.
## Ratio Test Indexes Indexes
## Obs 263 LR chi2 65.11 R2 0.313 C 0.798
## 0 186 d.f. 5 g 1.612 Dxy 0.597
## 1 77 Pr(> chi2) <0.0001 gr 5.014 gamma 0.615
## max |deriv| 7e-08 gp 0.246 tau-a 0.248
## Brier 0.161
##
## Coef S.E. Wald Z Pr(>|Z|)
## Intercept -4.6782 0.7166 -6.53 <0.0001
## tutha 0.9402 0.3380 2.78 0.0054
## giamalbumin 1.6556 0.4525 3.66 0.0003
## Aminosid 1.1909 0.4073 2.92 0.0035
## Furosemid 0.8139 0.3493 2.33 0.0198
## Lieuduytringaydau 0.2981 0.0831 3.59 0.0003
## MÔ HÌNH 2: BỎ BIẾN “LIỀU TÍCH LŨY” VÀ “SỐ NGÀY DÙNG”
xvars3 = thuy[,c(2:21)]
mohinh3 = bic.glm(xvars2, y , strict = F, OR = 20, glm.family = binomial, data = thuy)
summary(mohinh3)##
## Call:
## bic.glm.data.frame(x = xvars2, y = y, glm.family = binomial, strict = F, OR = 20, data = thuy)
##
##
## 49 models were selected
## Best 5 models (cumulative posterior probability = 0.4366 ):
##
## p!=0 EV SD model 1 model 2
## Intercept 100 -4.424404057 0.7496299 -4.6782 -4.0525
## tutha.x 89.5 0.940400473 0.4639185 0.9402 1.1322
## ShockNK.x 1.8 -0.000170457 0.0527365 . .
## giamalbumin.x 100.0 1.641724730 0.4532136 1.6556 1.6647
## tangbilirubin.x 2.5 0.011403897 0.1140149 . .
## ACEIARB.x 3.2 0.015922917 0.1196607 . .
## Aminosid.x 93.8 1.159584251 0.4979707 1.1909 1.3029
## Furosemid.x 52.8 0.446416631 0.4960618 0.8139 .
## vanmach.x 4.9 0.024041630 0.1394339 . .
## NSAIDs.x 2.1 0.004915733 0.0699036 . .
## Vancomycin.x 6.8 -0.055002562 0.2548914 . .
## Teicoplanin.x 6.3 0.079761981 0.3865728 . .
## Rifampicin.x 1.9 0.007669476 0.1304272 . .
## gioitinh.x 2.3 0.006008697 0.0658566 . .
## tuoi.x 2.2 0.000128454 0.0016753 . .
## Scrbandau.x 1.8 -0.000003341 0.0003362 . .
## THA1.x 2.2 0.004584979 0.0573597 . .
## DTD2.x 17.4 0.126711591 0.3193756 . .
## Lieuduytringaydau.x 100.0 0.281772212 0.0842971 0.2981 0.2598
## lieutu9MUI.x 2.4 -0.012462207 0.1317450 . .
## canquang.x 1.8 0.002692843 0.0974426 . .
## Songaydung.x 7.1 0.002183471 0.0098813 . .
##
## nVar 5 4
## BIC -1179.1291 -1179.0799
## post prob 0.144 0.140
## model 3 model 4 model 5
## Intercept -4.2512 -4.5340 -4.8189
## tutha.x 1.2033 . 1.0176
## ShockNK.x . . .
## giamalbumin.x 1.5623 1.8255 1.5703
## tangbilirubin.x . . .
## ACEIARB.x . . .
## Aminosid.x 1.2948 1.1549 1.2018
## Furosemid.x . 1.0309 0.7586
## vanmach.x . . .
## NSAIDs.x . . .
## Vancomycin.x . . .
## Teicoplanin.x . . .
## Rifampicin.x . . .
## gioitinh.x . . .
## tuoi.x . . .
## Scrbandau.x . . .
## THA1.x . . .
## DTD2.x 0.7536 . 0.6779
## Lieuduytringaydau.x 0.2791 0.2775 0.3125
## lieutu9MUI.x . . .
## canquang.x . . .
## Songaydung.x . . .
##
## nVar 5 4 6
## BIC -1177.4690 -1176.9035 -1176.6867
## post prob 0.063 0.047 0.042m3 = glm(doctinh ~tutha + giamalbumin + Aminosid + Furosemid + Lieuduytringaydau , family = binomial, data = thuy)
logistic.display(m3)##
## Logistic regression predicting doctinh
##
## crude OR(95%CI) adj. OR(95%CI)
## tutha: 1 vs 0 3.53 (1.97,6.34) 2.56 (1.32,4.97)
##
## giamalbumin: 1 vs 0 5.83 (2.65,12.82) 5.24 (2.16,12.71)
##
## Aminosid: 1 vs 0 3.27 (1.62,6.62) 3.29 (1.48,7.31)
##
## Furosemid: 1 vs 0 2.78 (1.56,4.96) 2.26 (1.14,4.47)
##
## Lieuduytringaydau (cont. var.) 1.27 (1.11,1.45) 1.35 (1.14,1.59)
##
## P(Wald's test) P(LR-test)
## tutha: 1 vs 0 0.005 0.005
##
## giamalbumin: 1 vs 0 < 0.001 < 0.001
##
## Aminosid: 1 vs 0 0.003 0.003
##
## Furosemid: 1 vs 0 0.02 0.018
##
## Lieuduytringaydau (cont. var.) < 0.001 < 0.001
##
## Log-likelihood = -126.4572
## No. of observations = 263
## AIC value = 264.9144f3 = lrm(doctinh ~tutha + giamalbumin + Aminosid + Furosemid + Lieuduytringaydau, data = thuy)
f3## Logistic Regression Model
##
## lrm(formula = doctinh ~ tutha + giamalbumin + Aminosid + Furosemid +
## Lieuduytringaydau, data = thuy)
##
## Model Likelihood Discrimination Rank Discrim.
## Ratio Test Indexes Indexes
## Obs 263 LR chi2 65.11 R2 0.313 C 0.798
## 0 186 d.f. 5 g 1.612 Dxy 0.597
## 1 77 Pr(> chi2) <0.0001 gr 5.014 gamma 0.615
## max |deriv| 7e-08 gp 0.246 tau-a 0.248
## Brier 0.161
##
## Coef S.E. Wald Z Pr(>|Z|)
## Intercept -4.6782 0.7166 -6.53 <0.0001
## tutha 0.9402 0.3380 2.78 0.0054
## giamalbumin 1.6556 0.4525 3.66 0.0003
## Aminosid 1.1909 0.4073 2.92 0.0035
## Furosemid 0.8139 0.3493 2.33 0.0198
## Lieuduytringaydau 0.2981 0.0831 3.59 0.0003
##