R_class
Phap
2023-03-13
data_fmh<-read.csv("/Users/phaptran/Documents/LEADING PROGRAM/N-DATA/ANALYSIS DTA/STATA ANALYSIS/R/CLASS/Framingham-dataset.csv",header=TRUE)
str(data_fmh)## 'data.frame': 11627 obs. of 39 variables:
## $ id : int 2448 2448 6238 6238 6238 9428 9428 10552 10552 11252 ...
## $ sex : int 1 1 2 2 2 1 1 2 2 2 ...
## $ tot.chol : int 195 209 250 260 237 245 283 225 232 285 ...
## $ age : int 39 52 46 52 58 48 54 61 67 46 ...
## $ sysbp : num 106 121 121 105 108 ...
## $ diasbp : num 70 66 81 69.5 66 80 89 95 109 84 ...
## $ smoker : int 0 0 0 0 0 1 1 1 1 1 ...
## $ cigs.day : int 0 0 0 0 0 20 30 30 20 23 ...
## $ bmi : num 27 NA 28.7 29.4 28.5 ...
## $ diabetes : int 0 0 0 0 0 0 0 0 0 0 ...
## $ bpmed : int 0 0 0 0 0 0 0 0 0 0 ...
## $ heart.rate : int 80 69 95 80 80 75 75 65 60 85 ...
## $ glucose : int 77 92 76 86 71 70 87 103 89 85 ...
## $ educ : int 4 4 2 2 2 1 1 3 3 3 ...
## $ prev.chd : int 0 0 0 0 0 0 0 0 0 0 ...
## $ prev.ap : int 0 0 0 0 0 0 0 0 0 0 ...
## $ prev.mi : int 0 0 0 0 0 0 0 0 0 0 ...
## $ prev.stroke : int 0 0 0 0 0 0 0 0 0 0 ...
## $ prev.hyp : int 0 0 0 0 0 0 0 1 1 0 ...
## $ time : int 0 4628 0 2156 4344 0 2199 0 1977 0 ...
## $ period : int 1 3 1 2 3 1 2 1 2 1 ...
## $ hdlc : int NA 31 NA NA 54 NA NA NA NA NA ...
## $ ldlc : int NA 178 NA NA 141 NA NA NA NA NA ...
## $ death : int 0 0 0 0 0 0 0 1 1 0 ...
## $ angina : int 0 0 0 0 0 0 0 0 0 0 ...
## $ hosp.mi : int 1 1 0 0 0 0 0 0 0 0 ...
## $ mi.fchd : int 1 1 0 0 0 0 0 0 0 0 ...
## $ any.chd : int 1 1 0 0 0 0 0 0 0 0 ...
## $ stroke : int 0 0 0 0 0 0 0 1 1 0 ...
## $ cvd : int 1 1 0 0 0 0 0 1 1 0 ...
## $ hypertension: int 0 0 0 0 0 0 0 1 1 1 ...
## $ time.ap : int 8766 8766 8766 8766 8766 8766 8766 2956 2956 8766 ...
## $ time.mi : int 6438 6438 8766 8766 8766 8766 8766 2956 2956 8766 ...
## $ time.mi.1 : int 6438 6438 8766 8766 8766 8766 8766 2956 2956 8766 ...
## $ time.chd : int 6438 6438 8766 8766 8766 8766 8766 2956 2956 8766 ...
## $ time.stroke : int 8766 8766 8766 8766 8766 8766 8766 2089 2089 8766 ...
## $ time.cvd : int 6438 6438 8766 8766 8766 8766 8766 2089 2089 8766 ...
## $ time.dth : int 8766 8766 8766 8766 8766 8766 8766 2956 2956 8766 ...
## $ time.hyp : int 8766 8766 8766 8766 8766 8766 8766 0 0 4285 ...head(data_fmh,n=10)## id sex tot.chol age sysbp diasbp smoker cigs.day bmi diabetes bpmed
## 1 2448 1 195 39 106.0 70.0 0 0 26.97 0 0
## 2 2448 1 209 52 121.0 66.0 0 0 NA 0 0
## 3 6238 2 250 46 121.0 81.0 0 0 28.73 0 0
## 4 6238 2 260 52 105.0 69.5 0 0 29.43 0 0
## 5 6238 2 237 58 108.0 66.0 0 0 28.50 0 0
## 6 9428 1 245 48 127.5 80.0 1 20 25.34 0 0
## 7 9428 1 283 54 141.0 89.0 1 30 25.34 0 0
## 8 10552 2 225 61 150.0 95.0 1 30 28.58 0 0
## 9 10552 2 232 67 183.0 109.0 1 20 30.18 0 0
## 10 11252 2 285 46 130.0 84.0 1 23 23.10 0 0
## heart.rate glucose educ prev.chd prev.ap prev.mi prev.stroke prev.hyp time
## 1 80 77 4 0 0 0 0 0 0
## 2 69 92 4 0 0 0 0 0 4628
## 3 95 76 2 0 0 0 0 0 0
## 4 80 86 2 0 0 0 0 0 2156
## 5 80 71 2 0 0 0 0 0 4344
## 6 75 70 1 0 0 0 0 0 0
## 7 75 87 1 0 0 0 0 0 2199
## 8 65 103 3 0 0 0 0 1 0
## 9 60 89 3 0 0 0 0 1 1977
## 10 85 85 3 0 0 0 0 0 0
## period hdlc ldlc death angina hosp.mi mi.fchd any.chd stroke cvd
## 1 1 NA NA 0 0 1 1 1 0 1
## 2 3 31 178 0 0 1 1 1 0 1
## 3 1 NA NA 0 0 0 0 0 0 0
## 4 2 NA NA 0 0 0 0 0 0 0
## 5 3 54 141 0 0 0 0 0 0 0
## 6 1 NA NA 0 0 0 0 0 0 0
## 7 2 NA NA 0 0 0 0 0 0 0
## 8 1 NA NA 1 0 0 0 0 1 1
## 9 2 NA NA 1 0 0 0 0 1 1
## 10 1 NA NA 0 0 0 0 0 0 0
## hypertension time.ap time.mi time.mi.1 time.chd time.stroke time.cvd
## 1 0 8766 6438 6438 6438 8766 6438
## 2 0 8766 6438 6438 6438 8766 6438
## 3 0 8766 8766 8766 8766 8766 8766
## 4 0 8766 8766 8766 8766 8766 8766
## 5 0 8766 8766 8766 8766 8766 8766
## 6 0 8766 8766 8766 8766 8766 8766
## 7 0 8766 8766 8766 8766 8766 8766
## 8 1 2956 2956 2956 2956 2089 2089
## 9 1 2956 2956 2956 2956 2089 2089
## 10 1 8766 8766 8766 8766 8766 8766
## time.dth time.hyp
## 1 8766 8766
## 2 8766 8766
## 3 8766 8766
## 4 8766 8766
## 5 8766 8766
## 6 8766 8766
## 7 8766 8766
## 8 2956 0
## 9 2956 0
## 10 8766 4285tail(data_fmh,n=10)## id sex tot.chol age sysbp diasbp smoker cigs.day bmi diabetes
## 11618 9993179 2 NA 50 131.0 80 1 25 21.22 0
## 11619 9993179 2 251 56 145.0 92 1 35 21.97 0
## 11620 9995546 2 269 52 133.5 83 0 0 21.47 0
## 11621 9995546 2 265 58 140.0 83 0 0 22.55 0
## 11622 9998212 1 185 40 141.0 98 0 0 25.60 0
## 11623 9998212 1 173 46 126.0 82 0 0 19.17 0
## 11624 9998212 1 153 52 143.0 89 0 0 25.74 0
## 11625 9999312 2 196 39 133.0 86 1 30 20.91 0
## 11626 9999312 2 240 46 138.0 79 1 20 26.39 0
## 11627 9999312 2 NA 50 147.0 96 1 10 24.19 0
## bpmed heart.rate glucose educ prev.chd prev.ap prev.mi prev.stroke
## 11618 0 75 NA 1 0 0 0 0
## 11619 1 95 90 1 0 0 0 0
## 11620 0 80 107 2 0 0 0 0
## 11621 1 80 79 2 0 0 0 0
## 11622 0 67 72 3 0 0 0 0
## 11623 0 70 NA 3 0 0 0 0
## 11624 0 65 72 3 0 0 0 0
## 11625 0 85 80 3 0 0 0 0
## 11626 0 90 83 3 0 0 0 0
## 11627 0 94 NA 3 0 0 0 0
## prev.hyp time period hdlc ldlc death angina hosp.mi mi.fchd any.chd
## 11618 0 2226 2 NA NA 1 0 0 0 0
## 11619 1 4396 3 70 181 1 0 0 0 0
## 11620 0 0 1 NA NA 0 1 0 1 1
## 11621 1 2186 2 NA NA 0 1 0 1 1
## 11622 1 0 1 NA NA 0 0 0 0 0
## 11623 1 2333 2 NA NA 0 0 0 0 0
## 11624 1 4538 3 30 123 0 0 0 0 0
## 11625 0 0 1 NA NA 0 0 0 0 0
## 11626 0 2390 2 NA NA 0 0 0 0 0
## 11627 1 4201 3 NA NA 0 0 0 0 0
## stroke cvd hypertension time.ap time.mi time.mi.1 time.chd time.stroke
## 11618 0 0 1 6729 6729 6729 6729 6729
## 11619 0 0 1 6729 6729 6729 6729 6729
## 11620 0 1 1 5939 8766 5209 5209 8766
## 11621 0 1 1 5939 8766 5209 5209 8766
## 11622 0 0 1 8766 8766 8766 8766 8766
## 11623 0 0 1 8766 8766 8766 8766 8766
## 11624 0 0 1 8766 8766 8766 8766 8766
## 11625 0 0 1 8766 8766 8766 8766 8766
## 11626 0 0 1 8766 8766 8766 8766 8766
## 11627 0 0 1 8766 8766 8766 8766 8766
## time.cvd time.dth time.hyp
## 11618 6729 6729 4396
## 11619 6729 6729 4396
## 11620 5209 8766 735
## 11621 5209 8766 735
## 11622 8766 8766 0
## 11623 8766 8766 0
## 11624 8766 8766 0
## 11625 8766 8766 4201
## 11626 8766 8766 4201
## 11627 8766 8766 4201library(table1)##
## Attaching package: 'table1'## The following objects are masked from 'package:base':
##
## units, units<-table1(~ sex + tot.chol + age + sysbp + diasbp + smoker + cigs.day + bmi + diabetes +
bpmed + heart.rate + glucose + educ + prev.chd + prev.ap + prev.mi +
prev.stroke + prev.hyp + time + period + hdlc + ldlc + death + angina +
hosp.mi + mi.fchd + any.chd + stroke + cvd + hypertension +
time.ap + time.mi + time.mi.1 + time.chd + time.stroke + time.cvd + time.dth + time.hyp, data_fmh)| Overall (N=11627) |
|
|---|---|
| sex | |
| Mean (SD) | 1.57 (0.495) |
| Median [Min, Max] | 2.00 [1.00, 2.00] |
| tot.chol | |
| Mean (SD) | 241 (45.4) |
| Median [Min, Max] | 238 [107, 696] |
| Missing | 409 (3.5%) |
| age | |
| Mean (SD) | 54.8 (9.56) |
| Median [Min, Max] | 54.0 [32.0, 81.0] |
| sysbp | |
| Mean (SD) | 136 (22.8) |
| Median [Min, Max] | 132 [83.5, 295] |
| diasbp | |
| Mean (SD) | 83.0 (11.7) |
| Median [Min, Max] | 82.0 [30.0, 150] |
| smoker | |
| Mean (SD) | 0.433 (0.495) |
| Median [Min, Max] | 0 [0, 1.00] |
| cigs.day | |
| Mean (SD) | 8.25 (12.2) |
| Median [Min, Max] | 0 [0, 90.0] |
| Missing | 79 (0.7%) |
| bmi | |
| Mean (SD) | 25.9 (4.10) |
| Median [Min, Max] | 25.5 [14.4, 56.8] |
| Missing | 52 (0.4%) |
| diabetes | |
| Mean (SD) | 0.0456 (0.209) |
| Median [Min, Max] | 0 [0, 1.00] |
| bpmed | |
| Mean (SD) | 0.0856 (0.280) |
| Median [Min, Max] | 0 [0, 1.00] |
| Missing | 593 (5.1%) |
| heart.rate | |
| Mean (SD) | 76.8 (12.5) |
| Median [Min, Max] | 75.0 [37.0, 220] |
| Missing | 6 (0.1%) |
| glucose | |
| Mean (SD) | 84.1 (25.0) |
| Median [Min, Max] | 80.0 [39.0, 478] |
| Missing | 1440 (12.4%) |
| educ | |
| Mean (SD) | 1.99 (1.03) |
| Median [Min, Max] | 2.00 [1.00, 4.00] |
| Missing | 295 (2.5%) |
| prev.chd | |
| Mean (SD) | 0.0724 (0.259) |
| Median [Min, Max] | 0 [0, 1.00] |
| prev.ap | |
| Mean (SD) | 0.0539 (0.226) |
| Median [Min, Max] | 0 [0, 1.00] |
| prev.mi | |
| Mean (SD) | 0.0322 (0.176) |
| Median [Min, Max] | 0 [0, 1.00] |
| prev.stroke | |
| Mean (SD) | 0.0131 (0.114) |
| Median [Min, Max] | 0 [0, 1.00] |
| prev.hyp | |
| Mean (SD) | 0.460 (0.498) |
| Median [Min, Max] | 0 [0, 1.00] |
| time | |
| Mean (SD) | 1960 (1760) |
| Median [Min, Max] | 2160 [0, 4850] |
| period | |
| Mean (SD) | 1.90 (0.807) |
| Median [Min, Max] | 2.00 [1.00, 3.00] |
| hdlc | |
| Mean (SD) | 49.4 (15.6) |
| Median [Min, Max] | 48.0 [10.0, 189] |
| Missing | 8600 (74.0%) |
| ldlc | |
| Mean (SD) | 176 (46.9) |
| Median [Min, Max] | 173 [20.0, 565] |
| Missing | 8601 (74.0%) |
| death | |
| Mean (SD) | 0.303 (0.460) |
| Median [Min, Max] | 0 [0, 1.00] |
| angina | |
| Mean (SD) | 0.164 (0.370) |
| Median [Min, Max] | 0 [0, 1.00] |
| hosp.mi | |
| Mean (SD) | 0.0993 (0.299) |
| Median [Min, Max] | 0 [0, 1.00] |
| mi.fchd | |
| Mean (SD) | 0.154 (0.361) |
| Median [Min, Max] | 0 [0, 1.00] |
| any.chd | |
| Mean (SD) | 0.272 (0.445) |
| Median [Min, Max] | 0 [0, 1.00] |
| stroke | |
| Mean (SD) | 0.0913 (0.288) |
| Median [Min, Max] | 0 [0, 1.00] |
| cvd | |
| Mean (SD) | 0.249 (0.433) |
| Median [Min, Max] | 0 [0, 1.00] |
| hypertension | |
| Mean (SD) | 0.743 (0.437) |
| Median [Min, Max] | 1.00 [0, 1.00] |
| time.ap | |
| Mean (SD) | 7240 (2480) |
| Median [Min, Max] | 8770 [0, 8770] |
| time.mi | |
| Mean (SD) | 7590 (2140) |
| Median [Min, Max] | 8770 [0, 8770] |
| time.mi.1 | |
| Mean (SD) | 7540 (2190) |
| Median [Min, Max] | 8770 [0, 8770] |
| time.chd | |
| Mean (SD) | 7010 (2640) |
| Median [Min, Max] | 8770 [0, 8770] |
| time.stroke | |
| Mean (SD) | 7660 (2010) |
| Median [Min, Max] | 8770 [0, 8770] |
| time.cvd | |
| Mean (SD) | 7170 (2540) |
| Median [Min, Max] | 8770 [0, 8770] |
| time.dth | |
| Mean (SD) | 7850 (1790) |
| Median [Min, Max] | 8770 [26.0, 8770] |
| time.hyp | |
| Mean (SD) | 3600 (3460) |
| Median [Min, Max] | 2430 [0, 8770] |
#Check factor for table 1
data_fmh$sex <- as.factor(data_fmh$sex)
data_fmh$smoker <- as.factor(data_fmh$smoker)
data_fmh$diabetes <- as.factor(data_fmh$diabetes)
data_fmh$bpmed <- as.factor(data_fmh$bpmed)
data_fmh$educ <- as.factor(data_fmh$educ)
data_fmh$prev.chd <- as.factor(data_fmh$prev.chd)
data_fmh$prev.ap <- as.factor(data_fmh$prev.ap)
data_fmh$prev.mi <- as.factor(data_fmh$prev.mi)
data_fmh$prev.stroke <- as.factor(data_fmh$prev.stroke)
data_fmh$prev.hyp <- as.factor(data_fmh$prev.hyp)
data_fmh$death <- as.factor(data_fmh$death)
data_fmh$period <- as.factor(data_fmh$period)
data_fmh$angina <- as.factor(data_fmh$angina)
data_fmh$hosp.mi <- as.factor(data_fmh$hosp.mi)
data_fmh$mi.fchd <- as.factor(data_fmh$mi.fchd)
data_fmh$any.chd <- as.factor(data_fmh$any.chd)
data_fmh$stroke <- as.factor(data_fmh$stroke)
data_fmh$cvd <- as.factor(data_fmh$cvd)
data_fmh$hypertension <- as.factor(data_fmh$hypertension)table1(~ sex + tot.chol + age + sysbp + diasbp + smoker + cigs.day + bmi + diabetes +
bpmed + heart.rate + glucose + educ + prev.chd + prev.ap + prev.mi +
prev.stroke + prev.hyp + time + period + hdlc + ldlc + death + angina +
hosp.mi + mi.fchd + any.chd + stroke + cvd + hypertension +
time.ap + time.mi + time.mi.1 + time.chd + time.stroke + time.cvd + time.dth + time.hyp, data_fmh)| Overall (N=11627) |
|
|---|---|
| sex | |
| 1 | 5022 (43.2%) |
| 2 | 6605 (56.8%) |
| tot.chol | |
| Mean (SD) | 241 (45.4) |
| Median [Min, Max] | 238 [107, 696] |
| Missing | 409 (3.5%) |
| age | |
| Mean (SD) | 54.8 (9.56) |
| Median [Min, Max] | 54.0 [32.0, 81.0] |
| sysbp | |
| Mean (SD) | 136 (22.8) |
| Median [Min, Max] | 132 [83.5, 295] |
| diasbp | |
| Mean (SD) | 83.0 (11.7) |
| Median [Min, Max] | 82.0 [30.0, 150] |
| smoker | |
| 0 | 6598 (56.7%) |
| 1 | 5029 (43.3%) |
| cigs.day | |
| Mean (SD) | 8.25 (12.2) |
| Median [Min, Max] | 0 [0, 90.0] |
| Missing | 79 (0.7%) |
| bmi | |
| Mean (SD) | 25.9 (4.10) |
| Median [Min, Max] | 25.5 [14.4, 56.8] |
| Missing | 52 (0.4%) |
| diabetes | |
| 0 | 11097 (95.4%) |
| 1 | 530 (4.6%) |
| bpmed | |
| 0 | 10090 (86.8%) |
| 1 | 944 (8.1%) |
| Missing | 593 (5.1%) |
| heart.rate | |
| Mean (SD) | 76.8 (12.5) |
| Median [Min, Max] | 75.0 [37.0, 220] |
| Missing | 6 (0.1%) |
| glucose | |
| Mean (SD) | 84.1 (25.0) |
| Median [Min, Max] | 80.0 [39.0, 478] |
| Missing | 1440 (12.4%) |
| educ | |
| 1 | 4690 (40.3%) |
| 2 | 3410 (29.3%) |
| 3 | 1885 (16.2%) |
| 4 | 1347 (11.6%) |
| Missing | 295 (2.5%) |
| prev.chd | |
| 0 | 10785 (92.8%) |
| 1 | 842 (7.2%) |
| prev.ap | |
| 0 | 11000 (94.6%) |
| 1 | 627 (5.4%) |
| prev.mi | |
| 0 | 11253 (96.8%) |
| 1 | 374 (3.2%) |
| prev.stroke | |
| 0 | 11475 (98.7%) |
| 1 | 152 (1.3%) |
| prev.hyp | |
| 0 | 6283 (54.0%) |
| 1 | 5344 (46.0%) |
| time | |
| Mean (SD) | 1960 (1760) |
| Median [Min, Max] | 2160 [0, 4850] |
| period | |
| 1 | 4434 (38.1%) |
| 2 | 3930 (33.8%) |
| 3 | 3263 (28.1%) |
| hdlc | |
| Mean (SD) | 49.4 (15.6) |
| Median [Min, Max] | 48.0 [10.0, 189] |
| Missing | 8600 (74.0%) |
| ldlc | |
| Mean (SD) | 176 (46.9) |
| Median [Min, Max] | 173 [20.0, 565] |
| Missing | 8601 (74.0%) |
| death | |
| 0 | 8100 (69.7%) |
| 1 | 3527 (30.3%) |
| angina | |
| 0 | 9725 (83.6%) |
| 1 | 1902 (16.4%) |
| hosp.mi | |
| 0 | 10473 (90.1%) |
| 1 | 1154 (9.9%) |
| mi.fchd | |
| 0 | 9839 (84.6%) |
| 1 | 1788 (15.4%) |
| any.chd | |
| 0 | 8469 (72.8%) |
| 1 | 3158 (27.2%) |
| stroke | |
| 0 | 10566 (90.9%) |
| 1 | 1061 (9.1%) |
| cvd | |
| 0 | 8728 (75.1%) |
| 1 | 2899 (24.9%) |
| hypertension | |
| 0 | 2985 (25.7%) |
| 1 | 8642 (74.3%) |
| time.ap | |
| Mean (SD) | 7240 (2480) |
| Median [Min, Max] | 8770 [0, 8770] |
| time.mi | |
| Mean (SD) | 7590 (2140) |
| Median [Min, Max] | 8770 [0, 8770] |
| time.mi.1 | |
| Mean (SD) | 7540 (2190) |
| Median [Min, Max] | 8770 [0, 8770] |
| time.chd | |
| Mean (SD) | 7010 (2640) |
| Median [Min, Max] | 8770 [0, 8770] |
| time.stroke | |
| Mean (SD) | 7660 (2010) |
| Median [Min, Max] | 8770 [0, 8770] |
| time.cvd | |
| Mean (SD) | 7170 (2540) |
| Median [Min, Max] | 8770 [0, 8770] |
| time.dth | |
| Mean (SD) | 7850 (1790) |
| Median [Min, Max] | 8770 [26.0, 8770] |
| time.hyp | |
| Mean (SD) | 3600 (3460) |
| Median [Min, Max] | 2430 [0, 8770] |
# plot(density(data$tot.chol))
plot(density(data_fmh$tot.chol, na.rm=TRUE), xlab="Total Cholesterol", main="Density Plot of Total Cholesterol")
qqnorm(data_fmh$tot.chol)
qqline(data_fmh$tot.chol, col = 2)
## Perform the Shapiro-Wilk test on tot.chol
#shapiro.test(data$tot.chol)
# Perform Anderson-Darling test
library(nortest)
ad.test(data_fmh$tot.chol)##
## Anderson-Darling normality test
##
## data: data_fmh$tot.chol
## A = 29.968, p-value < 2.2e-16cvm.test(data_fmh$tot.chol) #Note that the Cramer-von Mises test has similar assumptions to the Kolmogorov-Smirnov## Warning in cvm.test(data_fmh$tot.chol): p-value is smaller than 7.37e-10, cannot
## be computed more accurately##
## Cramer-von Mises normality test
##
## data: data_fmh$tot.chol
## W = 4.638, p-value = 7.37e-10# Perform Kolmogorov-Smirnov test
ks.test(data_fmh$tot.chol, "pnorm", mean(data_fmh$tot.chol), sd(data_fmh$tot.chol))## Warning in ks.test.default(data_fmh$tot.chol, "pnorm",
## mean(data_fmh$tot.chol), : ties should not be present for the Kolmogorov-Smirnov
## test##
## Asymptotic one-sample Kolmogorov-Smirnov test
##
## data: data_fmh$tot.chol
## D = NA, p-value = NA
## alternative hypothesis: two-sided##Check normal one-time##
library(magrittr) # needs to be run every time you start R and want to use %>%
library(dplyr) # alternatively, this also loads %>%##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(ggplot2)
library(reshape2)
# Plot histograms for each variable in the same plot
# Select the columns containing the numerical variables
num_vars <- c("tot.chol", "age", "sysbp", "diasbp", "cigs.day", "bmi", "heart.rate", "glucose")
data_num <- data_fmh %>% select(all_of(num_vars))
# Plot histograms for each variable in the same plot
ggplot(melt(data_num), aes(x=value, fill=variable)) +
geom_histogram(alpha=0.5, position="identity") +
facet_grid(variable ~ ., scales="free_y") +
labs(x="Value", y="Frequency")## No id variables; using all as measure variables## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.## Warning: Removed 1986 rows containing non-finite values (`stat_bin()`).
t.test(data_fmh$tot.chol ~ data_fmh$stroke)##
## Welch Two Sample t-test
##
## data: data_fmh$tot.chol by data_fmh$stroke
## t = -1.1019, df = 1201.4, p-value = 0.2707
## alternative hypothesis: true difference in means between group 0 and group 1 is not equal to 0
## 95 percent confidence interval:
## -4.951814 1.389933
## sample estimates:
## mean in group 0 mean in group 1
## 240.9992 242.7802wilcox.test(data_fmh$age ~ data_fmh$stroke)##
## Wilcoxon rank sum test with continuity correction
##
## data: data_fmh$age by data_fmh$stroke
## W = 3533309, p-value < 2.2e-16
## alternative hypothesis: true location shift is not equal to 0wilcox.test(data_fmh$sysbp ~ data_fmh$stroke)##
## Wilcoxon rank sum test with continuity correction
##
## data: data_fmh$sysbp by data_fmh$stroke
## W = 3523748, p-value < 2.2e-16
## alternative hypothesis: true location shift is not equal to 0wilcox.test(data_fmh$cigs.day ~ data_fmh$stroke)##
## Wilcoxon rank sum test with continuity correction
##
## data: data_fmh$cigs.day by data_fmh$stroke
## W = 5635544, p-value = 0.2572
## alternative hypothesis: true location shift is not equal to 0wilcox.test(data_fmh$bmi ~ data_fmh$stroke)##
## Wilcoxon rank sum test with continuity correction
##
## data: data_fmh$bmi by data_fmh$stroke
## W = 4868495, p-value = 1.479e-10
## alternative hypothesis: true location shift is not equal to 0wilcox.test(data_fmh$heart.rate ~ data_fmh$stroke)##
## Wilcoxon rank sum test with continuity correction
##
## data: data_fmh$heart.rate by data_fmh$stroke
## W = 5482066, p-value = 0.3083
## alternative hypothesis: true location shift is not equal to 0wilcox.test(data_fmh$glucose ~ data_fmh$stroke)##
## Wilcoxon rank sum test with continuity correction
##
## data: data_fmh$glucose by data_fmh$stroke
## W = 3997955, p-value = 4.127e-05
## alternative hypothesis: true location shift is not equal to 0#install.packages(“gtools”)
library(gmodels)
crosstable_result <- CrossTable(data_fmh$sex, data_fmh$stroke, chisq = TRUE)##
##
## Cell Contents
## |-------------------------|
## | N |
## | Chi-square contribution |
## | N / Row Total |
## | N / Col Total |
## | N / Table Total |
## |-------------------------|
##
##
## Total Observations in Table: 11627
##
##
## | data_fmh$stroke
## data_fmh$sex | 0 | 1 | Row Total |
## -------------|-----------|-----------|-----------|
## 1 | 4534 | 488 | 5022 |
## | 0.194 | 1.928 | |
## | 0.903 | 0.097 | 0.432 |
## | 0.429 | 0.460 | |
## | 0.390 | 0.042 | |
## -------------|-----------|-----------|-----------|
## 2 | 6032 | 573 | 6605 |
## | 0.147 | 1.466 | |
## | 0.913 | 0.087 | 0.568 |
## | 0.571 | 0.540 | |
## | 0.519 | 0.049 | |
## -------------|-----------|-----------|-----------|
## Column Total | 10566 | 1061 | 11627 |
## | 0.909 | 0.091 | |
## -------------|-----------|-----------|-----------|
##
##
## Statistics for All Table Factors
##
##
## Pearson's Chi-squared test
## ------------------------------------------------------------
## Chi^2 = 3.735296 d.f. = 1 p = 0.05327421
##
## Pearson's Chi-squared test with Yates' continuity correction
## ------------------------------------------------------------
## Chi^2 = 3.610699 d.f. = 1 p = 0.05740898
##
## crosstable_result <- CrossTable(data_fmh$smoker, data_fmh$stroke, chisq = TRUE)##
##
## Cell Contents
## |-------------------------|
## | N |
## | Chi-square contribution |
## | N / Row Total |
## | N / Col Total |
## | N / Table Total |
## |-------------------------|
##
##
## Total Observations in Table: 11627
##
##
## | data_fmh$stroke
## data_fmh$smoker | 0 | 1 | Row Total |
## ----------------|-----------|-----------|-----------|
## 0 | 5981 | 617 | 6598 |
## | 0.037 | 0.369 | |
## | 0.906 | 0.094 | 0.567 |
## | 0.566 | 0.582 | |
## | 0.514 | 0.053 | |
## ----------------|-----------|-----------|-----------|
## 1 | 4585 | 444 | 5029 |
## | 0.049 | 0.485 | |
## | 0.912 | 0.088 | 0.433 |
## | 0.434 | 0.418 | |
## | 0.394 | 0.038 | |
## ----------------|-----------|-----------|-----------|
## Column Total | 10566 | 1061 | 11627 |
## | 0.909 | 0.091 | |
## ----------------|-----------|-----------|-----------|
##
##
## Statistics for All Table Factors
##
##
## Pearson's Chi-squared test
## ------------------------------------------------------------
## Chi^2 = 0.9396167 d.f. = 1 p = 0.3323764
##
## Pearson's Chi-squared test with Yates' continuity correction
## ------------------------------------------------------------
## Chi^2 = 0.877662 d.f. = 1 p = 0.3488428
##
## crosstable_result <- CrossTable(data_fmh$diabetes, data_fmh$stroke, chisq = TRUE)##
##
## Cell Contents
## |-------------------------|
## | N |
## | Chi-square contribution |
## | N / Row Total |
## | N / Col Total |
## | N / Table Total |
## |-------------------------|
##
##
## Total Observations in Table: 11627
##
##
## | data_fmh$stroke
## data_fmh$diabetes | 0 | 1 | Row Total |
## ------------------|-----------|-----------|-----------|
## 0 | 10164 | 933 | 11097 |
## | 0.629 | 6.263 | |
## | 0.916 | 0.084 | 0.954 |
## | 0.962 | 0.879 | |
## | 0.874 | 0.080 | |
## ------------------|-----------|-----------|-----------|
## 1 | 402 | 128 | 530 |
## | 13.167 | 131.127 | |
## | 0.758 | 0.242 | 0.046 |
## | 0.038 | 0.121 | |
## | 0.035 | 0.011 | |
## ------------------|-----------|-----------|-----------|
## Column Total | 10566 | 1061 | 11627 |
## | 0.909 | 0.091 | |
## ------------------|-----------|-----------|-----------|
##
##
## Statistics for All Table Factors
##
##
## Pearson's Chi-squared test
## ------------------------------------------------------------
## Chi^2 = 151.1864 d.f. = 1 p = 9.542079e-35
##
## Pearson's Chi-squared test with Yates' continuity correction
## ------------------------------------------------------------
## Chi^2 = 149.2939 d.f. = 1 p = 2.473414e-34
##
## crosstable_result <- CrossTable(data_fmh$bpmed, data_fmh$stroke, chisq = TRUE)##
##
## Cell Contents
## |-------------------------|
## | N |
## | Chi-square contribution |
## | N / Row Total |
## | N / Col Total |
## | N / Table Total |
## |-------------------------|
##
##
## Total Observations in Table: 11034
##
##
## | data_fmh$stroke
## data_fmh$bpmed | 0 | 1 | Row Total |
## ---------------|-----------|-----------|-----------|
## 0 | 9288 | 802 | 10090 |
## | 1.470 | 14.683 | |
## | 0.921 | 0.079 | 0.914 |
## | 0.926 | 0.799 | |
## | 0.842 | 0.073 | |
## ---------------|-----------|-----------|-----------|
## 1 | 742 | 202 | 944 |
## | 15.709 | 156.936 | |
## | 0.786 | 0.214 | 0.086 |
## | 0.074 | 0.201 | |
## | 0.067 | 0.018 | |
## ---------------|-----------|-----------|-----------|
## Column Total | 10030 | 1004 | 11034 |
## | 0.909 | 0.091 | |
## ---------------|-----------|-----------|-----------|
##
##
## Statistics for All Table Factors
##
##
## Pearson's Chi-squared test
## ------------------------------------------------------------
## Chi^2 = 188.7973 d.f. = 1 p = 5.819098e-43
##
## Pearson's Chi-squared test with Yates' continuity correction
## ------------------------------------------------------------
## Chi^2 = 187.1747 d.f. = 1 p = 1.315389e-42
##
## crosstable_result <- CrossTable(data_fmh$educ, data_fmh$stroke, chisq = TRUE)##
##
## Cell Contents
## |-------------------------|
## | N |
## | Chi-square contribution |
## | N / Row Total |
## | N / Col Total |
## | N / Table Total |
## |-------------------------|
##
##
## Total Observations in Table: 11332
##
##
## | data_fmh$stroke
## data_fmh$educ | 0 | 1 | Row Total |
## --------------|-----------|-----------|-----------|
## 1 | 4146 | 544 | 4690 |
## | 3.138 | 31.220 | |
## | 0.884 | 0.116 | 0.414 |
## | 0.403 | 0.526 | |
## | 0.366 | 0.048 | |
## --------------|-----------|-----------|-----------|
## 2 | 3149 | 261 | 3410 |
## | 0.821 | 8.172 | |
## | 0.923 | 0.077 | 0.301 |
## | 0.306 | 0.252 | |
## | 0.278 | 0.023 | |
## --------------|-----------|-----------|-----------|
## 3 | 1752 | 133 | 1885 |
## | 0.896 | 8.910 | |
## | 0.929 | 0.071 | 0.166 |
## | 0.170 | 0.129 | |
## | 0.155 | 0.012 | |
## --------------|-----------|-----------|-----------|
## 4 | 1250 | 97 | 1347 |
## | 0.553 | 5.506 | |
## | 0.928 | 0.072 | 0.119 |
## | 0.121 | 0.094 | |
## | 0.110 | 0.009 | |
## --------------|-----------|-----------|-----------|
## Column Total | 10297 | 1035 | 11332 |
## | 0.909 | 0.091 | |
## --------------|-----------|-----------|-----------|
##
##
## Statistics for All Table Factors
##
##
## Pearson's Chi-squared test
## ------------------------------------------------------------
## Chi^2 = 59.21579 d.f. = 3 p = 8.645106e-13
##
##
## crosstable_result <- CrossTable(data_fmh$prev.chd, data_fmh$stroke, chisq = TRUE)##
##
## Cell Contents
## |-------------------------|
## | N |
## | Chi-square contribution |
## | N / Row Total |
## | N / Col Total |
## | N / Table Total |
## |-------------------------|
##
##
## Total Observations in Table: 11627
##
##
## | data_fmh$stroke
## data_fmh$prev.chd | 0 | 1 | Row Total |
## ------------------|-----------|-----------|-----------|
## 0 | 9887 | 898 | 10785 |
## | 0.758 | 7.544 | |
## | 0.917 | 0.083 | 0.928 |
## | 0.936 | 0.846 | |
## | 0.850 | 0.077 | |
## ------------------|-----------|-----------|-----------|
## 1 | 679 | 163 | 842 |
## | 9.703 | 96.627 | |
## | 0.806 | 0.194 | 0.072 |
## | 0.064 | 0.154 | |
## | 0.058 | 0.014 | |
## ------------------|-----------|-----------|-----------|
## Column Total | 10566 | 1061 | 11627 |
## | 0.909 | 0.091 | |
## ------------------|-----------|-----------|-----------|
##
##
## Statistics for All Table Factors
##
##
## Pearson's Chi-squared test
## ------------------------------------------------------------
## Chi^2 = 114.6319 d.f. = 1 p = 9.475184e-27
##
## Pearson's Chi-squared test with Yates' continuity correction
## ------------------------------------------------------------
## Chi^2 = 113.3053 d.f. = 1 p = 1.84979e-26
##
## crosstable_result <- CrossTable(data_fmh$prev.mi, data_fmh$stroke, chisq = TRUE)##
##
## Cell Contents
## |-------------------------|
## | N |
## | Chi-square contribution |
## | N / Row Total |
## | N / Col Total |
## | N / Table Total |
## |-------------------------|
##
##
## Total Observations in Table: 11627
##
##
## | data_fmh$stroke
## data_fmh$prev.mi | 0 | 1 | Row Total |
## -----------------|-----------|-----------|-----------|
## 0 | 10271 | 982 | 11253 |
## | 0.197 | 1.961 | |
## | 0.913 | 0.087 | 0.968 |
## | 0.972 | 0.926 | |
## | 0.883 | 0.084 | |
## -----------------|-----------|-----------|-----------|
## 1 | 295 | 79 | 374 |
## | 5.924 | 58.995 | |
## | 0.789 | 0.211 | 0.032 |
## | 0.028 | 0.074 | |
## | 0.025 | 0.007 | |
## -----------------|-----------|-----------|-----------|
## Column Total | 10566 | 1061 | 11627 |
## | 0.909 | 0.091 | |
## -----------------|-----------|-----------|-----------|
##
##
## Statistics for All Table Factors
##
##
## Pearson's Chi-squared test
## ------------------------------------------------------------
## Chi^2 = 67.07722 d.f. = 1 p = 2.610776e-16
##
## Pearson's Chi-squared test with Yates' continuity correction
## ------------------------------------------------------------
## Chi^2 = 65.59067 d.f. = 1 p = 5.550085e-16
##
## crosstable_result <- CrossTable(data_fmh$prev.stroke, data_fmh$stroke, chisq = TRUE)##
##
## Cell Contents
## |-------------------------|
## | N |
## | Chi-square contribution |
## | N / Row Total |
## | N / Col Total |
## | N / Table Total |
## |-------------------------|
##
##
## Total Observations in Table: 11627
##
##
## | data_fmh$stroke
## data_fmh$prev.stroke | 0 | 1 | Row Total |
## ---------------------|-----------|-----------|-----------|
## 0 | 10566 | 909 | 11475 |
## | 1.830 | 18.221 | |
## | 0.921 | 0.079 | 0.987 |
## | 1.000 | 0.857 | |
## | 0.909 | 0.078 | |
## ---------------------|-----------|-----------|-----------|
## 1 | 0 | 152 | 152 |
## | 138.130 | 1375.567 | |
## | 0.000 | 1.000 | 0.013 |
## | 0.000 | 0.143 | |
## | 0.000 | 0.013 | |
## ---------------------|-----------|-----------|-----------|
## Column Total | 10566 | 1061 | 11627 |
## | 0.909 | 0.091 | |
## ---------------------|-----------|-----------|-----------|
##
##
## Statistics for All Table Factors
##
##
## Pearson's Chi-squared test
## ------------------------------------------------------------
## Chi^2 = 1533.747 d.f. = 1 p = 0
##
## Pearson's Chi-squared test with Yates' continuity correction
## ------------------------------------------------------------
## Chi^2 = 1522.664 d.f. = 1 p = 0
##
## crosstable_result <- CrossTable(data_fmh$prev.hyp, data_fmh$stroke, chisq = TRUE)##
##
## Cell Contents
## |-------------------------|
## | N |
## | Chi-square contribution |
## | N / Row Total |
## | N / Col Total |
## | N / Table Total |
## |-------------------------|
##
##
## Total Observations in Table: 11627
##
##
## | data_fmh$stroke
## data_fmh$prev.hyp | 0 | 1 | Row Total |
## ------------------|-----------|-----------|-----------|
## 0 | 5995 | 288 | 6283 |
## | 14.260 | 142.011 | |
## | 0.954 | 0.046 | 0.540 |
## | 0.567 | 0.271 | |
## | 0.516 | 0.025 | |
## ------------------|-----------|-----------|-----------|
## 1 | 4571 | 773 | 5344 |
## | 16.766 | 166.963 | |
## | 0.855 | 0.145 | 0.460 |
## | 0.433 | 0.729 | |
## | 0.393 | 0.066 | |
## ------------------|-----------|-----------|-----------|
## Column Total | 10566 | 1061 | 11627 |
## | 0.909 | 0.091 | |
## ------------------|-----------|-----------|-----------|
##
##
## Statistics for All Table Factors
##
##
## Pearson's Chi-squared test
## ------------------------------------------------------------
## Chi^2 = 340.0001 d.f. = 1 p = 6.380538e-76
##
## Pearson's Chi-squared test with Yates' continuity correction
## ------------------------------------------------------------
## Chi^2 = 338.8096 d.f. = 1 p = 1.159122e-75
##
## crosstable_result <- CrossTable(data_fmh$hypertension, data_fmh$stroke, chisq = TRUE)##
##
## Cell Contents
## |-------------------------|
## | N |
## | Chi-square contribution |
## | N / Row Total |
## | N / Col Total |
## | N / Table Total |
## |-------------------------|
##
##
## Total Observations in Table: 11627
##
##
## | data_fmh$stroke
## data_fmh$hypertension | 0 | 1 | Row Total |
## ----------------------|-----------|-----------|-----------|
## 0 | 2890 | 95 | 2985 |
## | 11.600 | 115.523 | |
## | 0.968 | 0.032 | 0.257 |
## | 0.274 | 0.090 | |
## | 0.249 | 0.008 | |
## ----------------------|-----------|-----------|-----------|
## 1 | 7676 | 966 | 8642 |
## | 4.007 | 39.902 | |
## | 0.888 | 0.112 | 0.743 |
## | 0.726 | 0.910 | |
## | 0.660 | 0.083 | |
## ----------------------|-----------|-----------|-----------|
## Column Total | 10566 | 1061 | 11627 |
## | 0.909 | 0.091 | |
## ----------------------|-----------|-----------|-----------|
##
##
## Statistics for All Table Factors
##
##
## Pearson's Chi-squared test
## ------------------------------------------------------------
## Chi^2 = 171.0328 d.f. = 1 p = 4.401444e-39
##
## Pearson's Chi-squared test with Yates' continuity correction
## ------------------------------------------------------------
## Chi^2 = 170.07 d.f. = 1 p = 7.142933e-39
##
## #################################
table1(~ sex + tot.chol + age + sysbp + diasbp + smoker + cigs.day + bmi + diabetes +
bpmed + heart.rate + glucose + educ + prev.chd + prev.ap + prev.mi +
prev.stroke + prev.hyp + time + period + hdlc + ldlc + death + angina +
hosp.mi + mi.fchd + any.chd + cvd + hypertension |stroke, data_fmh)| 0 (N=10566) |
1 (N=1061) |
Overall (N=11627) |
|
|---|---|---|---|
| sex | |||
| 1 | 4534 (42.9%) | 488 (46.0%) | 5022 (43.2%) |
| 2 | 6032 (57.1%) | 573 (54.0%) | 6605 (56.8%) |
| tot.chol | |||
| Mean (SD) | 241 (44.9) | 243 (49.8) | 241 (45.4) |
| Median [Min, Max] | 238 [113, 638] | 240 [107, 696] | 238 [107, 696] |
| Missing | 376 (3.6%) | 33 (3.1%) | 409 (3.5%) |
| age | |||
| Mean (SD) | 54.2 (9.45) | 60.4 (8.90) | 54.8 (9.56) |
| Median [Min, Max] | 54.0 [32.0, 81.0] | 61.0 [34.0, 81.0] | 54.0 [32.0, 81.0] |
| sysbp | |||
| Mean (SD) | 135 (21.8) | 151 (26.9) | 136 (22.8) |
| Median [Min, Max] | 131 [83.5, 244] | 147 [94.0, 295] | 132 [83.5, 295] |
| diasbp | |||
| Mean (SD) | 82.5 (11.3) | 88.1 (14.0) | 83.0 (11.7) |
| Median [Min, Max] | 81.5 [30.0, 143] | 88.0 [51.5, 150] | 82.0 [30.0, 150] |
| smoker | |||
| 0 | 5981 (56.6%) | 617 (58.2%) | 6598 (56.7%) |
| 1 | 4585 (43.4%) | 444 (41.8%) | 5029 (43.3%) |
| cigs.day | |||
| Mean (SD) | 8.29 (12.2) | 7.86 (11.9) | 8.25 (12.2) |
| Median [Min, Max] | 0 [0, 90.0] | 0 [0, 80.0] | 0 [0, 90.0] |
| Missing | 72 (0.7%) | 7 (0.7%) | 79 (0.7%) |
| bmi | |||
| Mean (SD) | 25.8 (4.03) | 26.8 (4.68) | 25.9 (4.10) |
| Median [Min, Max] | 25.4 [14.4, 56.8] | 26.4 [16.9, 55.3] | 25.5 [14.4, 56.8] |
| Missing | 42 (0.4%) | 10 (0.9%) | 52 (0.4%) |
| diabetes | |||
| 0 | 10164 (96.2%) | 933 (87.9%) | 11097 (95.4%) |
| 1 | 402 (3.8%) | 128 (12.1%) | 530 (4.6%) |
| bpmed | |||
| 0 | 9288 (87.9%) | 802 (75.6%) | 10090 (86.8%) |
| 1 | 742 (7.0%) | 202 (19.0%) | 944 (8.1%) |
| Missing | 536 (5.1%) | 57 (5.4%) | 593 (5.1%) |
| heart.rate | |||
| Mean (SD) | 76.7 (12.4) | 77.4 (13.0) | 76.8 (12.5) |
| Median [Min, Max] | 75.0 [37.0, 220] | 75.0 [45.0, 135] | 75.0 [37.0, 220] |
| Missing | 3 (0.0%) | 3 (0.3%) | 6 (0.1%) |
| glucose | |||
| Mean (SD) | 83.6 (24.0) | 89.2 (33.1) | 84.1 (25.0) |
| Median [Min, Max] | 79.0 [39.0, 478] | 81.0 [40.0, 410] | 80.0 [39.0, 478] |
| Missing | 1320 (12.5%) | 120 (11.3%) | 1440 (12.4%) |
| educ | |||
| 1 | 4146 (39.2%) | 544 (51.3%) | 4690 (40.3%) |
| 2 | 3149 (29.8%) | 261 (24.6%) | 3410 (29.3%) |
| 3 | 1752 (16.6%) | 133 (12.5%) | 1885 (16.2%) |
| 4 | 1250 (11.8%) | 97 (9.1%) | 1347 (11.6%) |
| Missing | 269 (2.5%) | 26 (2.5%) | 295 (2.5%) |
| prev.chd | |||
| 0 | 9887 (93.6%) | 898 (84.6%) | 10785 (92.8%) |
| 1 | 679 (6.4%) | 163 (15.4%) | 842 (7.2%) |
| prev.ap | |||
| 0 | 10050 (95.1%) | 950 (89.5%) | 11000 (94.6%) |
| 1 | 516 (4.9%) | 111 (10.5%) | 627 (5.4%) |
| prev.mi | |||
| 0 | 10271 (97.2%) | 982 (92.6%) | 11253 (96.8%) |
| 1 | 295 (2.8%) | 79 (7.4%) | 374 (3.2%) |
| prev.stroke | |||
| 0 | 10566 (100%) | 909 (85.7%) | 11475 (98.7%) |
| 1 | 0 (0%) | 152 (14.3%) | 152 (1.3%) |
| prev.hyp | |||
| 0 | 5995 (56.7%) | 288 (27.1%) | 6283 (54.0%) |
| 1 | 4571 (43.3%) | 773 (72.9%) | 5344 (46.0%) |
| time | |||
| Mean (SD) | 1960 (1760) | 1900 (1750) | 1960 (1760) |
| Median [Min, Max] | 2160 [0, 4850] | 2150 [0, 4700] | 2160 [0, 4850] |
| period | |||
| 1 | 4019 (38.0%) | 415 (39.1%) | 4434 (38.1%) |
| 2 | 3567 (33.8%) | 363 (34.2%) | 3930 (33.8%) |
| 3 | 2980 (28.2%) | 283 (26.7%) | 3263 (28.1%) |
| hdlc | |||
| Mean (SD) | 49.6 (15.6) | 46.8 (15.2) | 49.4 (15.6) |
| Median [Min, Max] | 48.0 [10.0, 189] | 45.0 [11.0, 101] | 48.0 [10.0, 189] |
| Missing | 7799 (73.8%) | 801 (75.5%) | 8600 (74.0%) |
| ldlc | |||
| Mean (SD) | 177 (46.5) | 175 (50.3) | 176 (46.9) |
| Median [Min, Max] | 173 [20.0, 565] | 172 [58.0, 338] | 173 [20.0, 565] |
| Missing | 7800 (73.8%) | 801 (75.5%) | 8601 (74.0%) |
| death | |||
| 0 | 7707 (72.9%) | 393 (37.0%) | 8100 (69.7%) |
| 1 | 2859 (27.1%) | 668 (63.0%) | 3527 (30.3%) |
| angina | |||
| 0 | 8917 (84.4%) | 808 (76.2%) | 9725 (83.6%) |
| 1 | 1649 (15.6%) | 253 (23.8%) | 1902 (16.4%) |
| hosp.mi | |||
| 0 | 9602 (90.9%) | 871 (82.1%) | 10473 (90.1%) |
| 1 | 964 (9.1%) | 190 (17.9%) | 1154 (9.9%) |
| mi.fchd | |||
| 0 | 9059 (85.7%) | 780 (73.5%) | 9839 (84.6%) |
| 1 | 1507 (14.3%) | 281 (26.5%) | 1788 (15.4%) |
| any.chd | |||
| 0 | 7865 (74.4%) | 604 (56.9%) | 8469 (72.8%) |
| 1 | 2701 (25.6%) | 457 (43.1%) | 3158 (27.2%) |
| cvd | |||
| 0 | 8728 (82.6%) | 0 (0%) | 8728 (75.1%) |
| 1 | 1838 (17.4%) | 1061 (100%) | 2899 (24.9%) |
| hypertension | |||
| 0 | 2890 (27.4%) | 95 (9.0%) | 2985 (25.7%) |
| 1 | 7676 (72.6%) | 966 (91.0%) | 8642 (74.3%) |