rtPA2019
Hieu
1/5/2020
rtpa=read.csv("C:/Users/MAC/Downloads/thu thap so lieu rtPA 2019(3).csv")
attach(rtpa)
names(rtpa)## [1] "id" "Hotenbn" "tel"
## [4] "Thangnv" "mRSxv" "mRS90"
## [7] "mRS90caithien" "tv9Khong" "Thangtk"
## [10] "Toast" "gioi" "bddngv"
## [13] "tuoi" "cn" "cc"
## [16] "bmi" "Tdieutri" "Tcuakim"
## [19] "tha" "dtd" "rllp"
## [22] "smoke" "tsdotquy" "hattnv"
## [25] "hattrnv" "NIHSSnv" "NIHSS24h"
## [28] "NIHSSgiam4" "NIHSSxv" "mRSnv"
## [31] "mRSxv.1" "Glynv" "rungnhinv"
## [34] "ASPECTnv" "dautangquangCT" "hepmachcKhongynghia"
## [37] "NIHSScaithien" "xhn" "chaymaunhe"
## [40] "diung" "tvxv" "mRS90.1"
## [43] "mRS90caithien.1" "tv90" "X"summary(rtpa)## id Hotenbn tel Thangnv
## Min. : 1.0 ??ng Th? R? : 1 không có : 8 19-Apr :16
## 1st Qu.:20.5 Châu T Thu Trang: 1 : 3 19-Feb :10
## Median :40.0 D? Th? M?i : 1 377977628 : 2 19-Jul :10
## Mean :40.0 D??ng Ti?n Côn : 1 ` : 1 19-Jun : 8
## 3rd Qu.:59.5 D??ng V?n Hòa : 1 1247926894: 1 19-Mar : 7
## Max. :79.0 Hu?nh T Khiêm : 1 309973949 : 1 19-Aug : 6
## (Other) :73 (Other) :63 (Other):22
## mRSxv mRS90 mRS90caithien tv9Khong Thangtk
## Min. :0.000 Min. :0.000 Min. :0.0000 :24 19-Jul :15
## 1st Qu.:1.000 1st Qu.:0.000 1st Qu.:0.0000 Co : 6 19-May :10
## Median :2.000 Median :1.000 Median :1.0000 Khong:49 19-Oct :10
## Mean :2.506 Mean :1.509 Mean :0.7091 19-Nov : 8
## 3rd Qu.:4.000 3rd Qu.:2.500 3rd Qu.:1.0000 19-Sep : 8
## Max. :6.000 Max. :6.000 Max. :1.0000 19-Jun : 7
## NA's :24 NA's :24 (Other):21
## Toast gioi bddngv tuoi cn
## Khong Xd:35 Nam:47 Min. :0.00000 Min. :38.00 Min. :39.00
## MM l?n :17 Nu :32 1st Qu.:0.00000 1st Qu.:55.00 1st Qu.:53.00
## MM nho :19 Median :0.00000 Median :64.00 Median :58.00
## Tim : 8 Mean :0.03797 Mean :62.46 Mean :58.67
## 3rd Qu.:0.00000 3rd Qu.:69.50 3rd Qu.:64.50
## Max. :1.00000 Max. :79.00 Max. :84.00
##
## cc bmi Tdieutri Tcuakim tha
## Min. : 1.65 :75 Min. : 50.0 Min. : 10.00 Co :73
## 1st Qu.:150.00 #DIV/0!: 3 1st Qu.:140.0 1st Qu.: 40.00 Khong: 6
## Median :165.00 18 : 1 Median :170.0 Median : 50.00
## Mean :131.33 Mean :169.8 Mean : 53.08
## 3rd Qu.:170.00 3rd Qu.:200.0 3rd Qu.: 60.00
## Max. :170.00 Max. :328.0 Max. :130.00
## NA's :74
## dtd rllp smoke tsdotquy hattnv
## Co :13 Co :34 Co : 8 Co :11 Min. : 90.0
## Khong:66 Khong:45 Khong:71 Khong:68 1st Qu.:140.0
## Median :150.0
## Mean :153.8
## 3rd Qu.:160.0
## Max. :240.0
##
## hattrnv NIHSSnv NIHSS24h NIHSSgiam4
## Min. : 60.00 Min. : 4.00 Min. : 0.000 Co :34
## 1st Qu.: 80.00 1st Qu.: 6.00 1st Qu.: 2.000 Khong:45
## Median : 80.00 Median :10.00 Median : 7.000
## Mean : 85.22 Mean :11.48 Mean : 8.215
## 3rd Qu.: 90.00 3rd Qu.:15.50 3rd Qu.:12.000
## Max. :120.00 Max. :24.00 Max. :35.000
##
## NIHSSxv mRSnv mRSxv.1 Glynv
## Min. : 0.000 Min. :2.000 Min. :0.000 Min. : 52.0
## 1st Qu.: 1.000 1st Qu.:3.000 1st Qu.:1.000 1st Qu.: 98.5
## Median : 6.000 Median :4.000 Median :2.000 Median :117.0
## Mean : 7.734 Mean :3.532 Mean :2.494 Mean :131.7
## 3rd Qu.:11.500 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:136.5
## Max. :35.000 Max. :5.000 Max. :6.000 Max. :420.0
##
## rungnhinv ASPECTnv dautangquangCT hepmachcKhongynghia
## Co : 8 Min. : 7.000 Min. :0.00000 Co :18
## Khong:71 1st Qu.: 8.000 1st Qu.:0.00000 Khong:61
## Median : 9.000 Median :0.00000
## Mean : 8.722 Mean :0.03797
## 3rd Qu.: 9.500 3rd Qu.:0.00000
## Max. :10.000 Max. :1.00000
##
## NIHSScaithien xhn chaymaunhe diung tvxv mRS90.1
## Co :36 Khong:79 Co : 6 Khong:79 Co : 3 Min. :0.0
## Khong:43 Khong:73 Khong:76 1st Qu.:0.0
## Median :1.0
## Mean :0.6
## 3rd Qu.:1.0
## Max. :1.0
## NA's :74
## mRS90caithien.1 tv90 X
## Min. :0.0 Min. :0.0 :78
## 1st Qu.:0.0 1st Qu.:0.0 TV th8/19: 1
## Median :1.0 Median :0.5
## Mean :0.6 Mean :0.5
## 3rd Qu.:1.0 3rd Qu.:1.0
## Max. :1.0 Max. :1.0
## NA's :74 NA's :73hist(tuoi)
hist(Tdieutri)
hist(Tcuakim)
hist(NIHSSnv)
hist(NIHSS24h)
hist(NIHSSxv)
hist(mRSnv)
hist(mRSxv)
# Kiem dinh phan phoi chuan (p<0.05 --> không tuân theo lu???t phân ph???i chu???n)
shapiro.test(NIHSSnv) ##
## Shapiro-Wilk normality test
##
## data: NIHSSnv
## W = 0.86419, p-value = 5.715e-07summary(NIHSSnv)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 4.00 6.00 10.00 11.48 15.50 24.00summary(NIHSS24h)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.000 2.000 7.000 8.215 12.000 35.000summary(NIHSSxv)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.000 1.000 6.000 7.734 11.500 35.000summary(mRSnv)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 2.000 3.000 4.000 3.532 4.000 5.000summary(mRSxv)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.000 1.000 2.000 2.506 4.000 6.000summary(mRS90)## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## 0.000 0.000 1.000 1.509 2.500 6.000 24# Kiem dinh kg theo pp chuan
wilcox.test(NIHSSnv, NIHSS24h)##
## Wilcoxon rank sum test with continuity correction
##
## data: NIHSSnv and NIHSS24h
## W = 4149, p-value = 0.0003407
## alternative hypothesis: true location shift is not equal to 0wilcox.test(NIHSS24h, NIHSSxv)##
## Wilcoxon rank sum test with continuity correction
##
## data: NIHSS24h and NIHSSxv
## W = 3305, p-value = 0.5209
## alternative hypothesis: true location shift is not equal to 0wilcox.test(NIHSSnv, NIHSSxv)##
## Wilcoxon rank sum test with continuity correction
##
## data: NIHSSnv and NIHSSxv
## W = 4323, p-value = 2.788e-05
## alternative hypothesis: true location shift is not equal to 0wilcox.test(mRSnv, mRSxv)##
## Wilcoxon rank sum test with continuity correction
##
## data: mRSnv and mRSxv
## W = 4324, p-value = 1.945e-05
## alternative hypothesis: true location shift is not equal to 0wilcox.test(mRSxv, mRS90)##
## Wilcoxon rank sum test with continuity correction
##
## data: mRSxv and mRS90
## W = 2968.5, p-value = 0.0002503
## alternative hypothesis: true location shift is not equal to 0boxplot(NIHSSnv, col=c("red", "blue")) 
boxplot(NIHSSnv, NIHSS24h, NIHSSxv, col=c("red", "blue"), xlab= "NIHSS lúc NV, 24h, XV", ylab="Di???m NIHSS") 
# Kiem dinh bat cap
t.test(NIHSSnv, NIHSS24h, paired=TRUE)##
## Paired t-test
##
## data: NIHSSnv and NIHSS24h
## t = 5.4173, df = 78, p-value = 6.509e-07
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 2.065648 4.465998
## sample estimates:
## mean of the differences
## 3.265823t.test(NIHSSnv, NIHSSxv, paired = TRUE)##
## Paired t-test
##
## data: NIHSSnv and NIHSSxv
## t = 5.8394, df = 78, p-value = 1.144e-07
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 2.469421 5.024250
## sample estimates:
## mean of the differences
## 3.746835t.test(mRSnv, mRSxv, paired=TRUE)##
## Paired t-test
##
## data: mRSnv and mRSxv
## t = 6.2858, df = 78, p-value = 1.736e-08
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 0.7005793 1.3500536
## sample estimates:
## mean of the differences
## 1.025316table(tvxv)## tvxv
## Co Khong
## 3 76tapply(NIHSSnv, tvxv,mean)## Co Khong
## 20.00000 11.14474boxplot(NIHSSnv~ tvxv, xlab = "Tu vong luc xuat vien",ylab = "NIHSS luc nhap vien")
t.test(NIHSSnv ~ tvxv)##
## Welch Two Sample t-test
##
## data: NIHSSnv by tvxv
## t = 3.2374, df = 2.2846, p-value = 0.06999
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -1.614679 19.325205
## sample estimates:
## mean in group Co mean in group Khong
## 20.00000 11.14474# Kiem dinh tvxv
logistic =glm(tvxv ~ tuoi+ gioi+ NIHSSnv+ NIHSSxv+mRSnv, family = "binomial")
summary(logistic)##
## Call:
## glm(formula = tvxv ~ tuoi + gioi + NIHSSnv + NIHSSxv + mRSnv,
## family = "binomial")
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.24775 0.00488 0.01538 0.06868 1.29776
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 21.7287 11.3568 1.913 0.0557 .
## tuoi -0.1506 0.1193 -1.262 0.2068
## gioiNu -0.8745 1.7490 -0.500 0.6171
## NIHSSnv 0.2525 0.2627 0.961 0.3364
## NIHSSxv -0.5111 0.2824 -1.810 0.0703 .
## mRSnv -0.7892 1.6448 -0.480 0.6314
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 25.510 on 78 degrees of freedom
## Residual deviance: 10.113 on 73 degrees of freedom
## AIC: 22.113
##
## Number of Fisher Scoring iterations: 9## ty le % theo nhom
frequency= table(NIHSSgiam4)
frequency/sum(frequency)## NIHSSgiam4
## Co Khong
## 0.4303797 0.5696203summary(NIHSSgiam4)## Co Khong
## 34 45frequency= table(mRSnv)
frequency=table(mRSnv)
frequency/sum(frequency)## mRSnv
## 2 3 4 5
## 0.1518987 0.3417722 0.3291139 0.1772152summary(mRSnv)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 2.000 3.000 4.000 3.532 4.000 5.000table(mRSnv)## mRSnv
## 2 3 4 5
## 12 27 26 14frequency= table(mRSxv)
frequency=table(mRSxv)
frequency/sum(frequency)## mRSxv
## 0 1 2 3 4 5
## 0.11392405 0.22784810 0.17721519 0.20253165 0.11392405 0.12658228
## 6
## 0.03797468summary(mRSxv)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.000 1.000 2.000 2.506 4.000 6.000table(mRSxv)## mRSxv
## 0 1 2 3 4 5 6
## 9 18 14 16 9 10 3frequency=table(mRS90)
frequency/sum(frequency)## mRS90
## 0 1 2 3 4 5
## 0.47272727 0.18181818 0.09090909 0.03636364 0.12727273 0.01818182
## 6
## 0.07272727table(mRS90)## mRS90
## 0 1 2 3 4 5 6
## 26 10 5 2 7 1 4### Bang tong hop cac bien
library(table1)##
## Attaching package: 'table1'## The following objects are masked from 'package:base':
##
## units, units<-table1(~ tuoi+gioi+ tha+dtd+rllp+smoke+tsdotquy+ NIHSSnv +Tdieutri+Tcuakim+ Toast+ hattnv+Glynv+ NIHSS24h+mRSnv+mRSxv+NIHSScaithien+chaymaunhe)| Overall (n=79) |
|
|---|---|
| tuoi | |
| Mean (SD) | 62.5 (10.5) |
| Median [Min, Max] | 64.0 [38.0, 79.0] |
| gioi | |
| Nam | 47 (59.5%) |
| Nu | 32 (40.5%) |
| tha | |
| Co | 73 (92.4%) |
| Khong | 6 (7.6%) |
| dtd | |
| Co | 13 (16.5%) |
| Khong | 66 (83.5%) |
| rllp | |
| Co | 34 (43.0%) |
| Khong | 45 (57.0%) |
| smoke | |
| Co | 8 (10.1%) |
| Khong | 71 (89.9%) |
| tsdotquy | |
| Co | 11 (13.9%) |
| Khong | 68 (86.1%) |
| NIHSSnv | |
| Mean (SD) | 11.5 (6.22) |
| Median [Min, Max] | 10.0 [4.00, 24.0] |
| Tdieutri | |
| Mean (SD) | 170 (48.8) |
| Median [Min, Max] | 170 [50.0, 328] |
| Tcuakim | |
| Mean (SD) | 53.1 (23.0) |
| Median [Min, Max] | 50.0 [10.0, 130] |
| Toast | |
| Khong Xd | 35 (44.3%) |
| MM l?n | 17 (21.5%) |
| MM nho | 19 (24.1%) |
| Tim | 8 (10.1%) |
| hattnv | |
| Mean (SD) | 154 (29.2) |
| Median [Min, Max] | 150 [90.0, 240] |
| Glynv | |
| Mean (SD) | 132 (60.4) |
| Median [Min, Max] | 117 [52.0, 420] |
| NIHSS24h | |
| Mean (SD) | 8.22 (7.51) |
| Median [Min, Max] | 7.00 [0.00, 35.0] |
| mRSnv | |
| Mean (SD) | 3.53 (0.959) |
| Median [Min, Max] | 4.00 [2.00, 5.00] |
| mRSxv | |
| Mean (SD) | 2.51 (1.69) |
| Median [Min, Max] | 2.00 [0.00, 6.00] |
| NIHSScaithien | |
| Co | 36 (45.6%) |
| Khong | 43 (54.4%) |
| chaymaunhe | |
| Co | 6 (7.6%) |
| Khong | 73 (92.4%) |
summary(rtpa)## id Hotenbn tel Thangnv
## Min. : 1.0 ??ng Th? R? : 1 không có : 8 19-Apr :16
## 1st Qu.:20.5 Châu T Thu Trang: 1 : 3 19-Feb :10
## Median :40.0 D? Th? M?i : 1 377977628 : 2 19-Jul :10
## Mean :40.0 D??ng Ti?n Côn : 1 ` : 1 19-Jun : 8
## 3rd Qu.:59.5 D??ng V?n Hòa : 1 1247926894: 1 19-Mar : 7
## Max. :79.0 Hu?nh T Khiêm : 1 309973949 : 1 19-Aug : 6
## (Other) :73 (Other) :63 (Other):22
## mRSxv mRS90 mRS90caithien tv9Khong Thangtk
## Min. :0.000 Min. :0.000 Min. :0.0000 :24 19-Jul :15
## 1st Qu.:1.000 1st Qu.:0.000 1st Qu.:0.0000 Co : 6 19-May :10
## Median :2.000 Median :1.000 Median :1.0000 Khong:49 19-Oct :10
## Mean :2.506 Mean :1.509 Mean :0.7091 19-Nov : 8
## 3rd Qu.:4.000 3rd Qu.:2.500 3rd Qu.:1.0000 19-Sep : 8
## Max. :6.000 Max. :6.000 Max. :1.0000 19-Jun : 7
## NA's :24 NA's :24 (Other):21
## Toast gioi bddngv tuoi cn
## Khong Xd:35 Nam:47 Min. :0.00000 Min. :38.00 Min. :39.00
## MM l?n :17 Nu :32 1st Qu.:0.00000 1st Qu.:55.00 1st Qu.:53.00
## MM nho :19 Median :0.00000 Median :64.00 Median :58.00
## Tim : 8 Mean :0.03797 Mean :62.46 Mean :58.67
## 3rd Qu.:0.00000 3rd Qu.:69.50 3rd Qu.:64.50
## Max. :1.00000 Max. :79.00 Max. :84.00
##
## cc bmi Tdieutri Tcuakim tha
## Min. : 1.65 :75 Min. : 50.0 Min. : 10.00 Co :73
## 1st Qu.:150.00 #DIV/0!: 3 1st Qu.:140.0 1st Qu.: 40.00 Khong: 6
## Median :165.00 18 : 1 Median :170.0 Median : 50.00
## Mean :131.33 Mean :169.8 Mean : 53.08
## 3rd Qu.:170.00 3rd Qu.:200.0 3rd Qu.: 60.00
## Max. :170.00 Max. :328.0 Max. :130.00
## NA's :74
## dtd rllp smoke tsdotquy hattnv
## Co :13 Co :34 Co : 8 Co :11 Min. : 90.0
## Khong:66 Khong:45 Khong:71 Khong:68 1st Qu.:140.0
## Median :150.0
## Mean :153.8
## 3rd Qu.:160.0
## Max. :240.0
##
## hattrnv NIHSSnv NIHSS24h NIHSSgiam4
## Min. : 60.00 Min. : 4.00 Min. : 0.000 Co :34
## 1st Qu.: 80.00 1st Qu.: 6.00 1st Qu.: 2.000 Khong:45
## Median : 80.00 Median :10.00 Median : 7.000
## Mean : 85.22 Mean :11.48 Mean : 8.215
## 3rd Qu.: 90.00 3rd Qu.:15.50 3rd Qu.:12.000
## Max. :120.00 Max. :24.00 Max. :35.000
##
## NIHSSxv mRSnv mRSxv.1 Glynv
## Min. : 0.000 Min. :2.000 Min. :0.000 Min. : 52.0
## 1st Qu.: 1.000 1st Qu.:3.000 1st Qu.:1.000 1st Qu.: 98.5
## Median : 6.000 Median :4.000 Median :2.000 Median :117.0
## Mean : 7.734 Mean :3.532 Mean :2.494 Mean :131.7
## 3rd Qu.:11.500 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:136.5
## Max. :35.000 Max. :5.000 Max. :6.000 Max. :420.0
##
## rungnhinv ASPECTnv dautangquangCT hepmachcKhongynghia
## Co : 8 Min. : 7.000 Min. :0.00000 Co :18
## Khong:71 1st Qu.: 8.000 1st Qu.:0.00000 Khong:61
## Median : 9.000 Median :0.00000
## Mean : 8.722 Mean :0.03797
## 3rd Qu.: 9.500 3rd Qu.:0.00000
## Max. :10.000 Max. :1.00000
##
## NIHSScaithien xhn chaymaunhe diung tvxv mRS90.1
## Co :36 Khong:79 Co : 6 Khong:79 Co : 3 Min. :0.0
## Khong:43 Khong:73 Khong:76 1st Qu.:0.0
## Median :1.0
## Mean :0.6
## 3rd Qu.:1.0
## Max. :1.0
## NA's :74
## mRS90caithien.1 tv90 X
## Min. :0.0 Min. :0.0 :78
## 1st Qu.:0.0 1st Qu.:0.0 TV th8/19: 1
## Median :1.0 Median :0.5
## Mean :0.6 Mean :0.5
## 3rd Qu.:1.0 3rd Qu.:1.0
## Max. :1.0 Max. :1.0
## NA's :74 NA's :73table1(~ tha)| Overall (n=79) |
|
|---|---|
| tha | |
| Co | 73 (92.4%) |
| Khong | 6 (7.6%) |
table1(~hattrnv)| Overall (n=79) |
|
|---|---|
| hattrnv | |
| Mean (SD) | 85.2 (11.0) |
| Median [Min, Max] | 80.0 [60.0, 120] |
table1(~ Toast)| Overall (n=79) |
|
|---|---|
| Toast | |
| Khong Xd | 35 (44.3%) |
| MM l?n | 17 (21.5%) |
| MM nho | 19 (24.1%) |
| Tim | 8 (10.1%) |
library(table1)
hist(tuoi, col="blue", border="white") 
hist(tuoi, col="blue", border="white", xlab="Tuoi", ylab="Frequency", main="Phan bo theo do tuoi") 
hist(tuoi, prob=T, col="blue", border="white", xlab="Tuoi", ylab="Frequency", main="Phan bo theo do tuoi")
lines(density(tuoi), col="red", lwd=2)
hist(NIHSSnv, col="blue", border="white") 
hist(NIHSSnv, col="blue", border="white", xlab="NIHSS lúc NV", ylab="Frequency", main="Phân b??? t??? l??? NIHSS lúc NV") 
hist(NIHSSnv, prob=T, col="blue", border="white", xlab="NIHSS lúc NV", ylab="Frequency", main="Phân b??? t??? l??? NIHSS lúc NV")
lines(density(NIHSSnv), col="red", lwd=2)
boxplot(tuoi ~ gioi, col=c("red", "blue"))
boxplot(tuoi ~ gioi, col=c("red", "blue")) 
m0 = lm(tuoi ~ gioi, data=rtpa)
summary(m0)##
## Call:
## lm(formula = tuoi ~ gioi, data = rtpa)
##
## Residuals:
## Min 1Q Median 3Q Max
## -23.617 -7.152 1.383 7.848 17.383
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 61.617 1.537 40.097 <2e-16 ***
## gioiNu 2.070 2.414 0.858 0.394
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 10.54 on 77 degrees of freedom
## Multiple R-squared: 0.00946, Adjusted R-squared: -0.003405
## F-statistic: 0.7353 on 1 and 77 DF, p-value: 0.3938boxplot(NIHSSnv ~ NIHSSxv, col=c("red", "blue")) 
boxplot(mRSxv ~ gioi, col=c("red", "blue")) 
boxplot(mRSxv ~ gioi, col=c("red", "blue"), xlab="Gi???i tính", ylab = "Di???m", main="S??? di???m mRS lúc xu???t vi???n theo gi???i") 
###### moi tuong quan mRS XV theo thoi gian dieu tri
plot(Tdieutri~mRSxv)
plot(Tdieutri~mRSxv, pch=16, col="blue")
plot(Tdieutri~mRSxv, pch=16, col="blue", xlab="Di???m mRS xu???t vi???n", ylab="Th???i gian di???u tr???", main="M???i tuong quan gi???a th???i gian di???u tr??? và s??? di???m mRS xu???t vi???n")
abline(lm(Tdieutri~mRSxv), col="red", lwd=2)
plot(Tcuakim~mRSxv)
plot(Tcuakim~mRSxv, pch=16, col="blue", xlab="Di???m mRS xu???t vi???n", ylab="Th???i gian c???a kim", main="M???i tuong quan gi???a th???i gian c???a kim và s??? di???m mRS xu???t vi???n")
abline(lm(Tcuakim~mRSxv), col="red", lwd=2)
library(ggplot2)
p=ggplot(data= rtpa, aes(x=NIHSSnv))
p + geom_histogram()## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
p+ geom_histogram(col="white", fill="blue")+xlab("NIHSSnv")+ylab(("%"))+ggtitle( "M???t d??? phân b??? NIHSSnv")## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
p+ geom_histogram(aes(fill=..count..), col="white")+scale_fill_gradient("count", low= "green", high="red")## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
##### Ve bieu do
library(ggplot2)
p= ggplot(rtpa, aes(x=Tcuakim))
p= p+ geom_histogram()
p## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
p+ geom_histogram(col="white", fill="blue")+xlab("Thoi gian cua kim")+ylab(("Tan so"))+ggtitle( "Thoi gian cua kim")## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
p+ geom_histogram(col="white", fill="blue")+xlab("Thoi gian cua kim")+ylab(("Tan so"))+ggtitle( "Thoi gian cua kim")+theme_bw()## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
p+ geom_histogram(col="white", fill="blue")+xlab("Thoi gian cua kim")+ylab(("Tan so"))+ggtitle( "Thoi gian cua kim")+theme_replace()## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
p+ geom_histogram(aes(fill=..count..), col="white")+scale_fill_gradient("count", low= "green", high="red")+theme_update()## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
p+ geom_histogram(aes(fill=..count..), col="white")+scale_fill_gradient("count", low= "green", high="red")+xlab("Thoi gian cua kim")+ylab(("Tan so"))+ggtitle( "Thoi gian cua kim")+ theme_update()## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
summary(Tcuakim)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 10.00 40.00 50.00 53.08 60.00 130.00p= ggplot(rtpa, aes(x=Tcuakim))
p= p+ geom_histogram()
p## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
p+ geom_histogram(col="white", fill="blue")+xlab("Thoi gian cua kim")+ylab(("Tan so"))+ggtitle( "Thoi gian cua kim")## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
p+ geom_histogram(col="white", fill="blue")+xlab("Thoi gian cua kim")+ylab(("Tan so"))+ggtitle( "Thoi gian cua kim")+theme_bw()## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
p+ geom_histogram(col="white", fill="blue")+xlab("Thoi gian cua kim")+ylab(("Tan so"))+ggtitle( "Thoi gian cua kim")+theme_replace()## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
p+ geom_histogram(aes(fill=..count..), col="white")+scale_fill_gradient("count", low= "green", high="red")+theme_update()## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
p+ geom_histogram(aes(fill=..count..), col="white")+scale_fill_gradient("count", low= "green", high="red")+xlab("Thoi gian cua kim")+ylab(("Tan so"))+ggtitle( "Thoi gian cua kim")+ theme_update()## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
p= ggplot(rtpa, aes(x=mRSxv))
p= p+ geom_histogram()
p## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
p+ geom_histogram(col="white", fill="blue")+xlab("mRS xu???t vi???n")+ylab(("T??? l???"))+ggtitle( "T??? l??? s??? di???m mRS lúc xu???t vi???n")## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
p+ geom_histogram(col="white", fill="blue")+xlab("mRS xu???t vi???n")+ylab(("T??? l???"))+ggtitle( "T??? l??? s??? di???m mRS lúc xu???t vi???n")+theme_bw()## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
p+ geom_histogram(col="white", fill="blue")+xlab("mRS xu???t vi???n")+ylab(("T??? l???"))+ggtitle( "T??? l??? s??? di???m mRS lúc xu???t vi???n")+theme_replace()## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
p+ geom_histogram(aes(fill=..count..), col="white")+scale_fill_gradient("count", low= "green", high="red")+theme_update()## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
p+ geom_histogram(aes(fill=..count..), col="white")+scale_fill_gradient("count", low= "green", high="red")+xlab("mRS xu???t vi???n")+ylab("T??? l???")+ ggtitle("Bi???u d??? t??? l??? s??? di???m mRS lúc xu???t vi???n")+ theme_update()## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
#### Ve kieu boxplot thoi gian cua kim theo gioi
b= ggplot(rtpa, aes(x=gioi, y=Tcuakim))
b+ geom_boxplot()
b+ geom_boxplot(notch = T, notchwidth = 0.5, aes(fill= gioi))
#### outlier màu d???
b+ geom_boxplot(notch = T, notchwidth = 0.5, aes(fill= gioi), outlier.colour="red", outlier.size=3)
### v??? bieu do n???m + coord_flip()
b+ geom_boxplot(notch = T, notchwidth = 0.5, aes(fill= gioi), outlier.colour="red", outlier.size=3)+ coord_flip()
b+ geom_boxplot(notch = T, notchwidth = 0.5, aes(fill= gioi), outlier.colour="red", outlier.size=3)
## v??? bd c??? di???n BW
b+ geom_boxplot(notch = T, notchwidth = 0.5, aes(fill= gioi), outlier.colour="red", outlier.size=3)+ theme_replace()+theme_update()
#### V??? KI???U boxplot NIHSSnv theo gioi
b= ggplot(rtpa, aes(x=gioi, y=NIHSSnv))
b+ geom_boxplot()
b+ geom_boxplot(notch = T, notchwidth = 0.5, aes(fill= gioi))
#### outlier màu d???
b+ geom_boxplot(notch = T, notchwidth = 0.5, aes(fill= gioi), outlier.colour="red", outlier.size=3)
### v??? bieu do n???m + coord_flip()
b+ geom_boxplot(notch = T, notchwidth = 0.5, aes(fill= gioi), outlier.colour="red", outlier.size=3)+ coord_flip()
b+ geom_boxplot(notch = T, notchwidth = 0.5, aes(fill= gioi), outlier.colour="red", outlier.size=3)
## v??? bd c??? di???n BW
b+ geom_boxplot(notch = T, notchwidth = 0.5, aes(fill= gioi), outlier.colour="red", outlier.size=3)+ theme_replace()+theme_update()
#### V??? KI???U boxplot NIHSS 24 theo gioi
b= ggplot(rtpa, aes(x=gioi, y=NIHSS24h))
b+ geom_boxplot()
b+ geom_boxplot(notch = T, notchwidth = 0.5, aes(fill= gioi))
#### outlier màu d???
b+ geom_boxplot(notch = T, notchwidth = 0.5, aes(fill= gioi), outlier.colour="red", outlier.size=3)
### v??? bieu do n???m + coord_flip()
b+ geom_boxplot(notch = T, notchwidth = 0.5, aes(fill= gioi), outlier.colour="red", outlier.size=3)+ coord_flip()
b+ geom_boxplot(notch = T, notchwidth = 0.5, aes(fill= gioi), outlier.colour="red", outlier.size=3)
## v??? bd c??? di???n BW
b+ geom_boxplot(notch = T, notchwidth = 0.5, aes(fill= gioi), outlier.colour="red", outlier.size=3)+ theme_replace()+theme_update()
#### V??? KI???U boxplot mRSnv theo gioi
b= ggplot(rtpa, aes(x=gioi, y=mRSnv))
b+ geom_boxplot()
b+ geom_boxplot(notch = T, notchwidth = 0.5, aes(fill= gioi))## notch went outside hinges. Try setting notch=FALSE.## notch went outside hinges. Try setting notch=FALSE.
#### outlier màu d???
b+ geom_boxplot(notch = T, notchwidth = 0.5, aes(fill= gioi), outlier.colour="red", outlier.size=3)## notch went outside hinges. Try setting notch=FALSE.
## notch went outside hinges. Try setting notch=FALSE.
### v??? bieu do n???m + coord_flip()
b+ geom_boxplot(notch = T, notchwidth = 0.5, aes(fill= gioi), outlier.colour="red", outlier.size=3)+ coord_flip()## notch went outside hinges. Try setting notch=FALSE.
## notch went outside hinges. Try setting notch=FALSE.
b+ geom_boxplot(notch = T, notchwidth = 0.5, aes(fill= gioi), outlier.colour="red", outlier.size=3)## notch went outside hinges. Try setting notch=FALSE.
## notch went outside hinges. Try setting notch=FALSE.
## v??? bd c??? di???n BW
b+ geom_boxplot(notch = T, notchwidth = 0.5, aes(fill= gioi), outlier.colour="red", outlier.size=3)+ theme_replace()+theme_update()## notch went outside hinges. Try setting notch=FALSE.
## notch went outside hinges. Try setting notch=FALSE.
#### V??? KI???U boxplot mRS nv theo gioi
b= ggplot(rtpa, aes(x=gioi, y=mRSnv))
b+ geom_boxplot()
b+ geom_boxplot(notch = T, notchwidth = 1, aes(fill= gioi))## notch went outside hinges. Try setting notch=FALSE.
## notch went outside hinges. Try setting notch=FALSE.
#### outlier màu d???
b+ geom_boxplot(notch = T, notchwidth = 1, aes(fill= gioi), outlier.colour="red", outlier.size=3)## notch went outside hinges. Try setting notch=FALSE.
## notch went outside hinges. Try setting notch=FALSE.
### v??? bieu do n???m + coord_flip()
b+ geom_boxplot(notch = T, notchwidth = 1, aes(fill= gioi), outlier.colour="red", outlier.size=3)+ coord_flip()## notch went outside hinges. Try setting notch=FALSE.
## notch went outside hinges. Try setting notch=FALSE.
b+ geom_boxplot(notch = T, notchwidth = 1, aes(fill= gioi), outlier.colour="red", outlier.size=3)## notch went outside hinges. Try setting notch=FALSE.
## notch went outside hinges. Try setting notch=FALSE.
## v??? bd c??? di???n BW
b+ geom_boxplot(notch = T, notchwidth = 1, aes(fill= gioi), outlier.colour="red", outlier.size=3)+ theme_replace()+theme_update()## notch went outside hinges. Try setting notch=FALSE.
## notch went outside hinges. Try setting notch=FALSE.
#### V??? KI???U boxplot mRS XV theo gioi
b= ggplot(rtpa, aes(x=gioi, y=mRSxv))
b+ geom_boxplot()
b+ geom_boxplot(notch = T, notchwidth = 0.5, aes(fill= gioi))
#### outlier màu d???
b+ geom_boxplot(notch = T, notchwidth = 0.5, aes(fill= gioi), outlier.colour="red", outlier.size=3)
### v??? bieu do n???m + coord_flip()
b+ geom_boxplot(notch = T, notchwidth = 0.5, aes(fill= gioi), outlier.colour="red", outlier.size=3)+ coord_flip()
b+ geom_boxplot(notch = T, notchwidth = 0.5, aes(fill= gioi), outlier.colour="red", outlier.size=3)
## v??? bd c??? di???n BW
b+ geom_boxplot(notch = T, notchwidth = 0.5, aes(fill= gioi), outlier.colour="red", outlier.size=3)+ theme_replace()+theme_update()
head(rtpa)## id Hotenbn tel Thangnv mRSxv mRS90 mRS90caithien tv9Khong
## 1 1 Tr?n V Quang 983373643 18-Nov 2 0 1 Khong
## 2 2 Ph?m T Li?u Th?m 395593559 18-Dec 2 2 0 Khong
## 3 3 Nguy?n V K?nh 384749610 18-Dec 0 0 0 Khong
## 4 4 D??ng Ti?n Côn 948443123 18-Dec 0 0 0 Khong
## 5 5 Lê V C??ng 945525663 18-Dec 3 2 1 Khong
## 6 6 Nguy?n T Von 19-Jan 2 NA NA
## Thangtk Toast gioi bddngv tuoi cn cc bmi Tdieutri Tcuakim tha
## 1 19-Feb MM l?n Nam 0 51 50 1.65 18 180 130 Khong
## 2 19-Mar MM nho Nu 0 68 52 NA #DIV/0! 120 60 Co
## 3 19-Feb Khong Xd Nam 0 66 66 NA #DIV/0! 200 20 Co
## 4 19-Feb MM nho Nam 0 46 68 NA #DIV/0! 180 76 Co
## 5 19-Feb MM nho Nam 0 75 54 NA 165 55 Co
## 6 19-Apr Khong Xd Nu 0 73 58 NA 105 45 Co
## dtd rllp smoke tsdotquy hattnv hattrnv NIHSSnv NIHSS24h NIHSSgiam4
## 1 Khong Khong Khong Khong 150 80 8 7 Khong
## 2 Khong Co Khong Co 130 80 9 1 Co
## 3 Khong Khong Co Khong 160 90 5 0 Co
## 4 Khong Co Co Khong 210 100 6 0 Co
## 5 Khong Khong Khong Khong 140 70 6 6 Khong
## 6 Co Khong Khong Khong 160 90 5 2 Co
## NIHSSxv mRSnv mRSxv.1 Glynv rungnhinv ASPECTnv dautangquangCT
## 1 7 2 2 138 Khong 10 0
## 2 1 4 2 112 Khong 10 0
## 3 0 2 0 91 Khong 9 0
## 4 0 3 0 128 Khong 10 0
## 5 6 3 3 150 Khong 7 0
## 6 2 2 2 281 Khong 8 0
## hepmachcKhongynghia NIHSScaithien xhn chaymaunhe diung tvxv mRS90.1
## 1 Khong Khong Khong Khong Khong Khong NA
## 2 Khong Co Khong Khong Khong Khong NA
## 3 Khong Co Khong Khong Khong Khong 0
## 4 Khong Co Khong Khong Khong Khong 0
## 5 Khong Khong Khong Khong Khong Khong NA
## 6 Khong Khong Khong Co Khong Khong NA
## mRS90caithien.1 tv90 X
## 1 NA NA
## 2 NA 0 TV th8/19
## 3 0 0
## 4 0 0
## 5 NA NA
## 6 NA NAsummary(rtpa)## id Hotenbn tel Thangnv
## Min. : 1.0 ??ng Th? R? : 1 không có : 8 19-Apr :16
## 1st Qu.:20.5 Châu T Thu Trang: 1 : 3 19-Feb :10
## Median :40.0 D? Th? M?i : 1 377977628 : 2 19-Jul :10
## Mean :40.0 D??ng Ti?n Côn : 1 ` : 1 19-Jun : 8
## 3rd Qu.:59.5 D??ng V?n Hòa : 1 1247926894: 1 19-Mar : 7
## Max. :79.0 Hu?nh T Khiêm : 1 309973949 : 1 19-Aug : 6
## (Other) :73 (Other) :63 (Other):22
## mRSxv mRS90 mRS90caithien tv9Khong Thangtk
## Min. :0.000 Min. :0.000 Min. :0.0000 :24 19-Jul :15
## 1st Qu.:1.000 1st Qu.:0.000 1st Qu.:0.0000 Co : 6 19-May :10
## Median :2.000 Median :1.000 Median :1.0000 Khong:49 19-Oct :10
## Mean :2.506 Mean :1.509 Mean :0.7091 19-Nov : 8
## 3rd Qu.:4.000 3rd Qu.:2.500 3rd Qu.:1.0000 19-Sep : 8
## Max. :6.000 Max. :6.000 Max. :1.0000 19-Jun : 7
## NA's :24 NA's :24 (Other):21
## Toast gioi bddngv tuoi cn
## Khong Xd:35 Nam:47 Min. :0.00000 Min. :38.00 Min. :39.00
## MM l?n :17 Nu :32 1st Qu.:0.00000 1st Qu.:55.00 1st Qu.:53.00
## MM nho :19 Median :0.00000 Median :64.00 Median :58.00
## Tim : 8 Mean :0.03797 Mean :62.46 Mean :58.67
## 3rd Qu.:0.00000 3rd Qu.:69.50 3rd Qu.:64.50
## Max. :1.00000 Max. :79.00 Max. :84.00
##
## cc bmi Tdieutri Tcuakim tha
## Min. : 1.65 :75 Min. : 50.0 Min. : 10.00 Co :73
## 1st Qu.:150.00 #DIV/0!: 3 1st Qu.:140.0 1st Qu.: 40.00 Khong: 6
## Median :165.00 18 : 1 Median :170.0 Median : 50.00
## Mean :131.33 Mean :169.8 Mean : 53.08
## 3rd Qu.:170.00 3rd Qu.:200.0 3rd Qu.: 60.00
## Max. :170.00 Max. :328.0 Max. :130.00
## NA's :74
## dtd rllp smoke tsdotquy hattnv
## Co :13 Co :34 Co : 8 Co :11 Min. : 90.0
## Khong:66 Khong:45 Khong:71 Khong:68 1st Qu.:140.0
## Median :150.0
## Mean :153.8
## 3rd Qu.:160.0
## Max. :240.0
##
## hattrnv NIHSSnv NIHSS24h NIHSSgiam4
## Min. : 60.00 Min. : 4.00 Min. : 0.000 Co :34
## 1st Qu.: 80.00 1st Qu.: 6.00 1st Qu.: 2.000 Khong:45
## Median : 80.00 Median :10.00 Median : 7.000
## Mean : 85.22 Mean :11.48 Mean : 8.215
## 3rd Qu.: 90.00 3rd Qu.:15.50 3rd Qu.:12.000
## Max. :120.00 Max. :24.00 Max. :35.000
##
## NIHSSxv mRSnv mRSxv.1 Glynv
## Min. : 0.000 Min. :2.000 Min. :0.000 Min. : 52.0
## 1st Qu.: 1.000 1st Qu.:3.000 1st Qu.:1.000 1st Qu.: 98.5
## Median : 6.000 Median :4.000 Median :2.000 Median :117.0
## Mean : 7.734 Mean :3.532 Mean :2.494 Mean :131.7
## 3rd Qu.:11.500 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:136.5
## Max. :35.000 Max. :5.000 Max. :6.000 Max. :420.0
##
## rungnhinv ASPECTnv dautangquangCT hepmachcKhongynghia
## Co : 8 Min. : 7.000 Min. :0.00000 Co :18
## Khong:71 1st Qu.: 8.000 1st Qu.:0.00000 Khong:61
## Median : 9.000 Median :0.00000
## Mean : 8.722 Mean :0.03797
## 3rd Qu.: 9.500 3rd Qu.:0.00000
## Max. :10.000 Max. :1.00000
##
## NIHSScaithien xhn chaymaunhe diung tvxv mRS90.1
## Co :36 Khong:79 Co : 6 Khong:79 Co : 3 Min. :0.0
## Khong:43 Khong:73 Khong:76 1st Qu.:0.0
## Median :1.0
## Mean :0.6
## 3rd Qu.:1.0
## Max. :1.0
## NA's :74
## mRS90caithien.1 tv90 X
## Min. :0.0 Min. :0.0 :78
## 1st Qu.:0.0 1st Qu.:0.0 TV th8/19: 1
## Median :1.0 Median :0.5
## Mean :0.6 Mean :0.5
## 3rd Qu.:1.0 3rd Qu.:1.0
## Max. :1.0 Max. :1.0
## NA's :74 NA's :73# môi tuong quan NIHSSnv va mRSxv
p = ggplot(data=rtpa, aes(x=NIHSSnv, y=mRSxv))
p1 = p + geom_boxplot()
p2 = p + geom_point() + geom_smooth()
library(gridExtra)
grid.arrange(p1, p2, ncol=2)## Warning: Continuous x aesthetic -- did you forget aes(group=...)?## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
p = ggplot(data=rtpa, aes(x=NIHSS24h, y=mRSxv))
p1 = p + geom_boxplot()
p2 = p + geom_point() + geom_smooth()
grid.arrange(p1, p2, ncol=2)## Warning: Continuous x aesthetic -- did you forget aes(group=...)?## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
p = ggplot(data=rtpa, aes(x=mRSnv, y=mRSnv))
p1 = p + geom_boxplot()
p2 = p + geom_point() + geom_smooth()
library(gridExtra)
grid.arrange(p1, p2, ncol=2)## Warning: Continuous x aesthetic -- did you forget aes(group=...)?## `geom_smooth()` using method = 'loess' and formula 'y ~ x'## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : pseudoinverse used at 1.985## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : neighborhood radius 2.015## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : reciprocal condition number 2.0227e-016## Warning in simpleLoess(y, x, w, span, degree = degree, parametric =
## parametric, : There are other near singularities as well. 4.0602## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used
## at 1.985## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 2.015## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal
## condition number 2.0227e-016## Warning in predLoess(object$y, object$x, newx = if
## (is.null(newdata)) object$x else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other
## near singularities as well. 4.0602
p = ggplot(data=rtpa, aes(x=tuoi, y=mRSxv))
p1 = p + geom_point() + geom_smooth()
p2 = p + geom_point() + geom_smooth(method="lm", formula=y~x+I(x^2)+I(x^3))
grid.arrange(p1, p2, ncol=2)## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
# tuong quan da bien
# Bi???n c???n th??? hi???n
#vars= rtpa[, c("gioi", "tuoi", "Tdieutri", "Tcuakim", "NIHSSxv", "mRSvx", "ASPECTnv")]
# vars = rtpa[, c("gioi", "tuoi", "Tdieutri", "Tcuakim", "NIHSSxv", "mRSvx", "ASPECTnv")]
# V??? bi???u d??? tuong quan
library(GGally) ## Registered S3 method overwritten by 'GGally':
## method from
## +.gg ggplot2#ggpairs(data=rtpa, mapping = aes(color = gioi))
#summary(rtpa)
# Mói tuong quan da bi???n [lo???i b??? 2 bi???n s??? 1 và 2 (id, gender)]
dat = rtpa[, -c(1,2)]
library("GGally")
ggcorr(dat, label=T)## Warning in ggcorr(dat, label = T): data in column(s) 'tel', 'Thangnv',
## 'tv9Khong', 'Thangtk', 'Toast', 'gioi', 'bmi', 'tha', 'dtd', 'rllp',
## 'smoke', 'tsdotquy', 'NIHSSgiam4', 'rungnhinv', 'hepmachcKhongynghia',
## 'NIHSScaithien', 'xhn', 'chaymaunhe', 'diung', 'tvxv', 'X' are not numeric
## and were ignored## Warning in cor(data, use = method[1], method = method[2]): the standard
## deviation is zero
#ggpairs(rtpa)
dat = rtpa[, -c(1,2)]
library(psych)##
## Attaching package: 'psych'## The following objects are masked from 'package:ggplot2':
##
## %+%, alpha#pairs.panels(dat)
#???nh hu???ng c???a tu???i mRSvx ?
m1 = lm(mRSxv ~ tuoi, data=rtpa)
summary(m1)##
## Call:
## lm(formula = mRSxv ~ tuoi, data = rtpa)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.666 -1.450 -0.176 1.180 3.853
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.70545 1.14335 0.617 0.539
## tuoi 0.02883 0.01806 1.597 0.114
##
## Residual standard error: 1.677 on 77 degrees of freedom
## Multiple R-squared: 0.03206, Adjusted R-squared: 0.01949
## F-statistic: 2.55 on 1 and 77 DF, p-value: 0.1144#Khác bi???t v??? mRSxv nam và n??? ?
m2 = lm(mRSxv~ gioi, data=rtpa)
summary(m2)##
## Call:
## lm(formula = mRSxv ~ gioi, data = rtpa)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.8750 -1.2553 -0.2553 1.1250 3.7447
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.2553 0.2446 9.222 4.48e-14 ***
## gioiNu 0.6197 0.3842 1.613 0.111
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.677 on 77 degrees of freedom
## Multiple R-squared: 0.03267, Adjusted R-squared: 0.02011
## F-statistic: 2.601 on 1 and 77 DF, p-value: 0.1109# ==> N??? có mRSxv l???n hon nam 25% (SE 0.4%%), và s??? khác bi???t này có ý nghia th???ng kê (P < 0.0001)
m3=lm(Tcuakim ~ mRSxv, data=rtpa)
summary(m3)##
## Call:
## lm(formula = Tcuakim ~ mRSxv, data = rtpa)
##
## Residuals:
## Min 1Q Median 3Q Max
## -41.366 -14.136 -3.636 8.864 77.499
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 50.231 4.652 10.798 <2e-16 ***
## mRSxv 1.135 1.541 0.737 0.464
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 23.05 on 77 degrees of freedom
## Multiple R-squared: 0.006998, Adjusted R-squared: -0.005898
## F-statistic: 0.5426 on 1 and 77 DF, p-value: 0.4636# mRSxv tang, thoi gian cua kim tang 0.76% (SE 1.69), và m???i liên quan này có ý nghia th???ng kê (P < 0.0001)
m3=lm(Tcuakim ~ mRSxv, data=rtpa)
plot(rtpa$Tcuakim ~rtpa$mRSxv, pch=16, col="blue")
abline(m3, col="red")
# Kiem tra gia d???nh mo hinh
m3=lm(mRSxv ~ NIHSSnv, data=rtpa)
library(ggfortify)
autoplot(m3)
# Phan tich don bi???n
summary(lm(mRSxv~NIHSSnv), data=rtpa)##
## Call:
## lm(formula = mRSxv ~ NIHSSnv)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.3443 -1.0825 0.0047 1.0504 2.9770
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.82072 0.34089 2.408 0.0185 *
## NIHSSnv 0.14682 0.02615 5.615 2.98e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.436 on 77 degrees of freedom
## Multiple R-squared: 0.2905, Adjusted R-squared: 0.2813
## F-statistic: 31.53 on 1 and 77 DF, p-value: 2.98e-07summary(lm(mRSxv~ NIHSS24h), data= rtpa)##
## Call:
## lm(formula = mRSxv ~ NIHSS24h)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.6587 -0.4207 -0.1054 0.5793 1.9238
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.9113 0.1453 6.271 1.93e-08 ***
## NIHSS24h 0.1942 0.0131 14.825 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.8683 on 77 degrees of freedom
## Multiple R-squared: 0.7405, Adjusted R-squared: 0.7372
## F-statistic: 219.8 on 1 and 77 DF, p-value: < 2.2e-16summary(lm(mRSxv~ NIHSSxv), data= rtpa)##
## Call:
## lm(formula = mRSxv ~ NIHSSxv)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.8910 -0.4475 -0.1513 0.4663 1.8361
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.97893 0.12423 7.88 1.73e-11 ***
## NIHSSxv 0.19749 0.01146 17.23 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7736 on 77 degrees of freedom
## Multiple R-squared: 0.794, Adjusted R-squared: 0.7914
## F-statistic: 296.9 on 1 and 77 DF, p-value: < 2.2e-16summary(lm(mRSxv~ mRSnv), data= rtpa)##
## Call:
## lm(formula = mRSxv ~ mRSnv)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.93589 -1.01872 0.06411 1.06411 3.06411
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.7328 0.6295 -1.164 0.248
## mRSnv 0.9172 0.1721 5.329 9.52e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.457 on 77 degrees of freedom
## Multiple R-squared: 0.2695, Adjusted R-squared: 0.26
## F-statistic: 28.4 on 1 and 77 DF, p-value: 9.521e-07# phan tich da bien
m4 = lm(mRSxv ~ NIHSSnv+ NIHSS24h +mRSnv, data=rtpa)
summary(m4)##
## Call:
## lm(formula = mRSxv ~ NIHSSnv + NIHSS24h + mRSnv, data = rtpa)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.63870 -0.36748 0.02531 0.56683 1.77765
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.39576 0.39599 0.999 0.32080
## NIHSSnv -0.08207 0.02847 -2.883 0.00514 **
## NIHSS24h 0.21581 0.01787 12.075 < 2e-16 ***
## mRSnv 0.36239 0.15893 2.280 0.02544 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.8334 on 75 degrees of freedom
## Multiple R-squared: 0.7672, Adjusted R-squared: 0.7579
## F-statistic: 82.39 on 3 and 75 DF, p-value: < 2.2e-16# giai thich
#mRSxv=0.39-0.08NIHSSSnv+0.21NIHSS24h+0.36mRSnv
# moi diem NIHSSnv giam co lien quan den 8% giam diem mRSxv
# moi diem NIHSS24h tang co lien quan den 21% tang diem mRSxv,
# moi diem mRSnv tang co lq den 36% tang diem mRSxv.
# Ba yeu to NIHSSnv, NIHSS24h, mRSnv giai thich 76% khac biet ve mRSxv giua cac bn.
summary(rtpa)## id Hotenbn tel Thangnv
## Min. : 1.0 ??ng Th? R? : 1 không có : 8 19-Apr :16
## 1st Qu.:20.5 Châu T Thu Trang: 1 : 3 19-Feb :10
## Median :40.0 D? Th? M?i : 1 377977628 : 2 19-Jul :10
## Mean :40.0 D??ng Ti?n Côn : 1 ` : 1 19-Jun : 8
## 3rd Qu.:59.5 D??ng V?n Hòa : 1 1247926894: 1 19-Mar : 7
## Max. :79.0 Hu?nh T Khiêm : 1 309973949 : 1 19-Aug : 6
## (Other) :73 (Other) :63 (Other):22
## mRSxv mRS90 mRS90caithien tv9Khong Thangtk
## Min. :0.000 Min. :0.000 Min. :0.0000 :24 19-Jul :15
## 1st Qu.:1.000 1st Qu.:0.000 1st Qu.:0.0000 Co : 6 19-May :10
## Median :2.000 Median :1.000 Median :1.0000 Khong:49 19-Oct :10
## Mean :2.506 Mean :1.509 Mean :0.7091 19-Nov : 8
## 3rd Qu.:4.000 3rd Qu.:2.500 3rd Qu.:1.0000 19-Sep : 8
## Max. :6.000 Max. :6.000 Max. :1.0000 19-Jun : 7
## NA's :24 NA's :24 (Other):21
## Toast gioi bddngv tuoi cn
## Khong Xd:35 Nam:47 Min. :0.00000 Min. :38.00 Min. :39.00
## MM l?n :17 Nu :32 1st Qu.:0.00000 1st Qu.:55.00 1st Qu.:53.00
## MM nho :19 Median :0.00000 Median :64.00 Median :58.00
## Tim : 8 Mean :0.03797 Mean :62.46 Mean :58.67
## 3rd Qu.:0.00000 3rd Qu.:69.50 3rd Qu.:64.50
## Max. :1.00000 Max. :79.00 Max. :84.00
##
## cc bmi Tdieutri Tcuakim tha
## Min. : 1.65 :75 Min. : 50.0 Min. : 10.00 Co :73
## 1st Qu.:150.00 #DIV/0!: 3 1st Qu.:140.0 1st Qu.: 40.00 Khong: 6
## Median :165.00 18 : 1 Median :170.0 Median : 50.00
## Mean :131.33 Mean :169.8 Mean : 53.08
## 3rd Qu.:170.00 3rd Qu.:200.0 3rd Qu.: 60.00
## Max. :170.00 Max. :328.0 Max. :130.00
## NA's :74
## dtd rllp smoke tsdotquy hattnv
## Co :13 Co :34 Co : 8 Co :11 Min. : 90.0
## Khong:66 Khong:45 Khong:71 Khong:68 1st Qu.:140.0
## Median :150.0
## Mean :153.8
## 3rd Qu.:160.0
## Max. :240.0
##
## hattrnv NIHSSnv NIHSS24h NIHSSgiam4
## Min. : 60.00 Min. : 4.00 Min. : 0.000 Co :34
## 1st Qu.: 80.00 1st Qu.: 6.00 1st Qu.: 2.000 Khong:45
## Median : 80.00 Median :10.00 Median : 7.000
## Mean : 85.22 Mean :11.48 Mean : 8.215
## 3rd Qu.: 90.00 3rd Qu.:15.50 3rd Qu.:12.000
## Max. :120.00 Max. :24.00 Max. :35.000
##
## NIHSSxv mRSnv mRSxv.1 Glynv
## Min. : 0.000 Min. :2.000 Min. :0.000 Min. : 52.0
## 1st Qu.: 1.000 1st Qu.:3.000 1st Qu.:1.000 1st Qu.: 98.5
## Median : 6.000 Median :4.000 Median :2.000 Median :117.0
## Mean : 7.734 Mean :3.532 Mean :2.494 Mean :131.7
## 3rd Qu.:11.500 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:136.5
## Max. :35.000 Max. :5.000 Max. :6.000 Max. :420.0
##
## rungnhinv ASPECTnv dautangquangCT hepmachcKhongynghia
## Co : 8 Min. : 7.000 Min. :0.00000 Co :18
## Khong:71 1st Qu.: 8.000 1st Qu.:0.00000 Khong:61
## Median : 9.000 Median :0.00000
## Mean : 8.722 Mean :0.03797
## 3rd Qu.: 9.500 3rd Qu.:0.00000
## Max. :10.000 Max. :1.00000
##
## NIHSScaithien xhn chaymaunhe diung tvxv mRS90.1
## Co :36 Khong:79 Co : 6 Khong:79 Co : 3 Min. :0.0
## Khong:43 Khong:73 Khong:76 1st Qu.:0.0
## Median :1.0
## Mean :0.6
## 3rd Qu.:1.0
## Max. :1.0
## NA's :74
## mRS90caithien.1 tv90 X
## Min. :0.0 Min. :0.0 :78
## 1st Qu.:0.0 1st Qu.:0.0 TV th8/19: 1
## Median :1.0 Median :0.5
## Mean :0.6 Mean :0.5
## 3rd Qu.:1.0 3rd Qu.:1.0
## Max. :1.0 Max. :1.0
## NA's :74 NA's :73# Chonn mô hinh tot nhat mRSxv
library(BMA)## Loading required package: survival## Loading required package: leaps## Loading required package: robustbase##
## Attaching package: 'robustbase'## The following object is masked from 'package:survival':
##
## heart## The following object is masked from 'package:psych':
##
## cushny## Loading required package: inline## Loading required package: rrcov## Scalable Robust Estimators with High Breakdown Point (version 1.4-7)yvar = rtpa[, ("mRSxv")]
xvars = rtpa[, c("gioi", "tuoi", "Tdieutri", "Tcuakim", "NIHSSnv")]
bma = bicreg(xvars, yvar, strict=FALSE, OR=20)
summary(bma)##
## Call:
## bicreg(x = xvars, y = yvar, strict = FALSE, OR = 20)
##
##
## 7 models were selected
## Best 5 models (cumulative posterior probability = 0.9283 ):
##
## p!=0 EV SD model 1 model 2 model 3
## Intercept 100.0 6.200e-01 0.716090 0.820720 0.642877 -0.362615
## gioiNu 26.2 1.327e-01 0.278727 . 0.508921 .
## tuoi 16.8 3.200e-03 0.009548 . . 0.019611
## Tdieutri 9.7 -2.167e-04 0.001237 . . .
## Tcuakim 5.6 -8.041e-05 0.001749 . . .
## NIHSSnv 100.0 1.458e-01 0.026224 0.146817 0.144352 0.143204
##
## nVar 1 2 2
## r2 0.291 0.312 0.305
## BIC -22.746280 -20.859589 -20.025199
## post prob 0.489 0.190 0.125
## model 4 model 5
## Intercept 1.157364 0.885189
## gioiNu . .
## tuoi . .
## Tdieutri -0.002077 .
## Tcuakim . -0.001432
## NIHSSnv 0.148220 0.147823
##
## nVar 2 2
## r2 0.294 0.291
## BIC -18.774239 -18.416929
## post prob 0.067 0.056imageplot.bma(bma)
# Chon mô hinh tot nhat 2
library(BMA)
yvar = rtpa[, ("mRSxv")]
xvars = rtpa[, c("Tdieutri","Tcuakim","NIHSSnv", "NIHSS24h", "mRSnv")]
bma = bicreg(xvars, yvar, strict=FALSE, OR=20)
summary(bma)##
## Call:
## bicreg(x = xvars, y = yvar, strict = FALSE, OR = 20)
##
##
## 10 models were selected
## Best 5 models (cumulative posterior probability = 0.8513 ):
##
## p!=0 EV SD model 1 model 2
## Intercept 100.0 8.053e-01 0.4392503 9.113e-01 3.958e-01
## Tdieutri 9.8 -9.546e-05 0.0006938 . .
## Tcuakim 9.3 -1.336e-04 0.0014010 . .
## NIHSSnv 57.0 -3.727e-02 0.0410661 . -8.207e-02
## NIHSS24h 100.0 2.067e-01 0.0197505 1.942e-01 2.158e-01
## mRSnv 38.8 1.286e-01 0.1967720 . 3.624e-01
##
## nVar 1 3
## r2 0.741 0.767
## BIC -1.022e+02 -1.020e+02
## post prob 0.308 0.282
## model 3 model 4 model 5
## Intercept 1.175e+00 1.120e+00 1.027e+00
## Tdieutri . -1.237e-03 .
## Tcuakim . . -2.326e-03
## NIHSSnv -3.968e-02 . .
## NIHSS24h 2.175e-01 1.944e-01 1.951e-01
## mRSnv . . .
##
## nVar 2 2 2
## r2 0.751 0.742 0.742
## BIC -1.011e+02 -9.823e+01 -9.814e+01
## post prob 0.178 0.042 0.040imageplot.bma(bma)