a_DCI_PD_STS_v8
Dihua Xu
Jun 2, 2016
## dat$trt
## group1 group2 group3
## 17 44 67## Variable trt=group1 trt=group2 trt=group3 P.Value
## 1 age 43.8 + 12.9 (17) 52.9 + 14 (44) 54.8 + 12.6 (67) 0.004
## 2 sex_M 3/17 (17.6 %) 12/43 (27.9 %) 19/67 (28.4 %) 0.658
## 3 sex_F 14/17 (82.4 %) 31/43 (72.1 %) 48/67 (71.6 %) NA
## 4 race_White 6/16 (37.5 %) 25/41 (61 %) 45/67 (67.2 %) 0.091
## 5 race_Non-White 10/16 (62.5 %) 16/41 (39 %) 22/67 (32.8 %) NA
## 6 bmi 28.1 + 7.1 (16) 32.5 + 6.8 (40) 33.2 + 7.6 (66) 0.057
## 7 diabetes_FALSE 13/17 (76.5 %) 26/43 (60.5 %) 38/67 (56.7 %) 0.330
## 8 diabetes_TRUE 4/17 (23.5 %) 17/43 (39.5 %) 29/67 (43.3 %) NAall time
Survival by STS (yes, no)
## Call: survfit(formula = Surv(time2death, death) ~ trt, data = dat)
##
## n events median 0.95LCL 0.95UCL
## trt=group1 17 6 2.256 1.864 NA
## trt=group2 44 27 0.723 0.356 NA
## trt=group3 67 49 0.742 0.490 2.19
## Call: survfit(formula = Surv(time2death, death) ~ trt, data = dat)
##
## trt=group1
## time n.risk n.event survival std.err lower 95% CI upper 95% CI
## 0.0 17 0 1.000 0.0000 1.0000 1
## 0.5 12 2 0.857 0.0935 0.6921 1
## 1.0 9 1 0.786 0.1097 0.5977 1
## 2.0 4 1 0.655 0.1505 0.4173 1
## 3.0 2 1 0.491 0.1812 0.2383 1
## 4.0 1 1 0.246 0.1958 0.0514 1
##
## trt=group2
## time n.risk n.event survival std.err lower 95% CI upper 95% CI
## 0.0 44 0 1.000 0.0000 1.0000 1.000
## 0.5 23 15 0.632 0.0759 0.4999 0.800
## 1.0 12 7 0.432 0.0821 0.2972 0.626
## 2.0 4 3 0.320 0.0826 0.1927 0.530
## 3.0 2 1 0.213 0.1029 0.0827 0.549
## 4.0 1 0 0.213 0.1029 0.0827 0.549
##
## trt=group3
## time n.risk n.event survival std.err lower 95% CI upper 95% CI
## 0.0 67 0 1.000 0.0000 1.000 1.000
## 0.5 35 27 0.578 0.0621 0.469 0.714
## 1.0 29 6 0.479 0.0633 0.370 0.621
## 2.0 21 6 0.379 0.0620 0.275 0.522
## 3.0 13 3 0.322 0.0607 0.223 0.466
## 4.0 10 2 0.269 0.0613 0.172 0.420
## 5.0 9 0 0.269 0.0613 0.172 0.420## Call:
## coxph(formula = Surv(time2death, death) ~ trt, data = dat)
##
## n= 128, number of events= 82
##
## coef exp(coef) se(coef) z Pr(>|z|)
## trtgroup2 0.9138 2.4937 0.4526 2.019 0.0435 *
## trtgroup3 0.7474 2.1116 0.4370 1.711 0.0872 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## exp(coef) exp(-coef) lower .95 upper .95
## trtgroup2 2.494 0.4010 1.0270 6.055
## trtgroup3 2.112 0.4736 0.8967 4.972
##
## Concordance= 0.548 (se = 0.033 )
## Rsquare= 0.038 (max possible= 0.994 )
## Likelihood ratio test= 4.97 on 2 df, p=0.08334
## Wald test = 4.08 on 2 df, p=0.1303
## Score (logrank) test = 4.29 on 2 df, p=0.1169Death or Hospitalization by STS (yes, no)
## Call: survfit(formula = Surv(time2death, death.or.hosp) ~ trt, data = dat)
##
## n events median 0.95LCL 0.95UCL
## trt=group1 17 7 2.256 1.292 NA
## trt=group2 44 32 0.723 0.356 1.16
## trt=group3 67 59 0.742 0.400 1.88
## Call: survfit(formula = Surv(time2death, death.or.hosp) ~ trt, data = dat)
##
## trt=group1
## time n.risk n.event survival std.err lower 95% CI upper 95% CI
## 0.0 17 0 1.000 0.0000 1.000 1.000
## 0.5 12 2 0.857 0.0935 0.692 1.000
## 1.0 9 1 0.786 0.1097 0.598 1.000
## 2.0 4 2 0.573 0.1523 0.340 0.965
## 3.0 2 1 0.430 0.1686 0.199 0.927
## 4.0 1 1 0.215 0.1737 0.044 1.000
##
## trt=group2
## time n.risk n.event survival std.err lower 95% CI upper 95% CI
## 0.0 44 0 1.0000 0.0000 1.0000 1.000
## 0.5 23 16 0.6061 0.0772 0.4722 0.778
## 1.0 12 8 0.3840 0.0801 0.2552 0.578
## 2.0 4 5 0.2032 0.0736 0.0999 0.413
## 3.0 2 1 0.1354 0.0739 0.0465 0.395
## 4.0 1 1 0.0677 0.0605 0.0118 0.390
##
## trt=group3
## time n.risk n.event survival std.err lower 95% CI upper 95% CI
## 0.0 67 0 1.000 0.0000 1.0000 1.000
## 0.5 35 28 0.565 0.0620 0.4559 0.701
## 1.0 29 6 0.468 0.0628 0.3602 0.609
## 2.0 21 7 0.355 0.0605 0.2538 0.495
## 3.0 13 8 0.220 0.0531 0.1367 0.353
## 4.0 10 3 0.169 0.0482 0.0965 0.295
## 5.0 9 1 0.152 0.0462 0.0837 0.276## Call:
## coxph(formula = Surv(time2death, death.or.hosp) ~ trt, data = dat)
##
## n= 128, number of events= 98
##
## coef exp(coef) se(coef) z Pr(>|z|)
## trtgroup2 0.9756 2.6529 0.4187 2.33 0.0198 *
## trtgroup3 0.7037 2.0213 0.4044 1.74 0.0818 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## exp(coef) exp(-coef) lower .95 upper .95
## trtgroup2 2.653 0.3770 1.1677 6.027
## trtgroup3 2.021 0.4947 0.9149 4.465
##
## Concordance= 0.554 (se = 0.031 )
## Rsquare= 0.05 (max possible= 0.997 )
## Likelihood ratio test= 6.54 on 2 df, p=0.03795
## Wald test = 5.6 on 2 df, p=0.06095
## Score (logrank) test = 5.88 on 2 df, p=0.05294Two year survival
Survival by STS (yes, no)
## Call: survfit(formula = Surv(fu2y, death2y) ~ trt, data = dat)
##
## n events median 0.95LCL 0.95UCL
## trt=group1 17 4 NA 1.864 NA
## trt=group2 44 25 0.723 0.356 NA
## trt=group3 67 39 0.742 0.490 NA
## Call: survfit(formula = Surv(fu2y, death2y) ~ trt, data = dat)
##
## trt=group1
## time n.risk n.event survival std.err lower 95% CI upper 95% CI
## 0.0 17 0 1.000 0.0000 1.000 1
## 0.5 12 2 0.857 0.0935 0.692 1
## 1.0 9 1 0.786 0.1097 0.598 1
## 2.0 4 1 0.655 0.1505 0.417 1
##
## trt=group2
## time n.risk n.event survival std.err lower 95% CI upper 95% CI
## 0.0 44 0 1.000 0.0000 1.000 1.000
## 0.5 23 15 0.632 0.0759 0.500 0.800
## 1.0 12 7 0.432 0.0821 0.297 0.626
## 2.0 4 3 0.320 0.0826 0.193 0.530
##
## trt=group3
## time n.risk n.event survival std.err lower 95% CI upper 95% CI
## 0.0 67 0 1.000 0.0000 1.000 1.000
## 0.5 35 27 0.578 0.0621 0.469 0.714
## 1.0 29 6 0.479 0.0633 0.370 0.621
## 2.0 21 6 0.379 0.0620 0.275 0.522## Call:
## coxph(formula = Surv(fu2y, death2y) ~ trt, data = dat)
##
## n= 128, number of events= 68
##
## coef exp(coef) se(coef) z Pr(>|z|)
## trtgroup2 1.2073 3.3445 0.5394 2.238 0.0252 *
## trtgroup3 1.1405 3.1282 0.5252 2.171 0.0299 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## exp(coef) exp(-coef) lower .95 upper .95
## trtgroup2 3.345 0.2990 1.162 9.627
## trtgroup3 3.128 0.3197 1.117 8.757
##
## Concordance= 0.551 (se = 0.034 )
## Rsquare= 0.056 (max possible= 0.99 )
## Likelihood ratio test= 7.34 on 2 df, p=0.02545
## Wald test = 5.18 on 2 df, p=0.07485
## Score (logrank) test = 5.79 on 2 df, p=0.0552## Call:
## coxph(formula = Surv(fu2y, death2y) ~ trt + age + bmi, data = dat)
##
## n= 122, number of events= 65
## (6 observations deleted due to missingness)
##
## coef exp(coef) se(coef) z Pr(>|z|)
## trtgroup2 0.930513 2.535810 0.555626 1.675 0.0940 .
## trtgroup3 0.820974 2.272712 0.537218 1.528 0.1265
## age 0.016045 1.016174 0.009403 1.706 0.0879 .
## bmi 0.020325 1.020532 0.017640 1.152 0.2493
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## exp(coef) exp(-coef) lower .95 upper .95
## trtgroup2 2.536 0.3944 0.8534 7.535
## trtgroup3 2.273 0.4400 0.7930 6.514
## age 1.016 0.9841 0.9976 1.035
## bmi 1.021 0.9799 0.9859 1.056
##
## Concordance= 0.617 (se = 0.038 )
## Rsquare= 0.081 (max possible= 0.99 )
## Likelihood ratio test= 10.33 on 4 df, p=0.03527
## Wald test = 8.54 on 4 df, p=0.07382
## Score (logrank) test = 9.04 on 4 df, p=0.06017## Call:
## coxph(formula = Surv(fu2y, death2y) ~ trt + age + sex + race +
## bmi + diabetes, data = dat)
##
## n= 119, number of events= 63
## (9 observations deleted due to missingness)
##
## coef exp(coef) se(coef) z Pr(>|z|)
## trtgroup2 0.770390 2.160608 0.562090 1.371 0.171
## trtgroup3 0.747919 2.112599 0.537651 1.391 0.164
## age 0.007861 1.007892 0.010240 0.768 0.443
## sexF -0.104235 0.901013 0.289813 -0.360 0.719
## raceNon-White -0.072478 0.930086 0.282257 -0.257 0.797
## bmi 0.016041 1.016170 0.018858 0.851 0.395
## diabetesTRUE 0.545965 1.726273 0.273604 1.995 0.046 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## exp(coef) exp(-coef) lower .95 upper .95
## trtgroup2 2.1606 0.4628 0.7180 6.502
## trtgroup3 2.1126 0.4734 0.7365 6.060
## age 1.0079 0.9922 0.9879 1.028
## sexF 0.9010 1.1099 0.5106 1.590
## raceNon-White 0.9301 1.0752 0.5349 1.617
## bmi 1.0162 0.9841 0.9793 1.054
## diabetesTRUE 1.7263 0.5793 1.0098 2.951
##
## Concordance= 0.625 (se = 0.039 )
## Rsquare= 0.105 (max possible= 0.989 )
## Likelihood ratio test= 13.25 on 7 df, p=0.06632
## Wald test = 12.07 on 7 df, p=0.09817
## Score (logrank) test = 12.83 on 7 df, p=0.07629Death or Hospitalization by STS (yes, no)
## Call: survfit(formula = Surv(fu2y, death.or.hosp.2y) ~ trt, data = dat)
##
## n events median 0.95LCL 0.95UCL
## trt=group1 17 5 NA 1.292 NA
## trt=group2 44 29 0.723 0.356 1.16
## trt=group3 67 41 0.742 0.400 1.88
## Call: survfit(formula = Surv(fu2y, death.or.hosp.2y) ~ trt, data = dat)
##
## trt=group1
## time n.risk n.event survival std.err lower 95% CI upper 95% CI
## 0.0 17 0 1.000 0.0000 1.000 1.000
## 0.5 12 2 0.857 0.0935 0.692 1.000
## 1.0 9 1 0.786 0.1097 0.598 1.000
## 2.0 4 2 0.573 0.1523 0.340 0.965
##
## trt=group2
## time n.risk n.event survival std.err lower 95% CI upper 95% CI
## 0.0 44 0 1.000 0.0000 1.0000 1.000
## 0.5 23 16 0.606 0.0772 0.4722 0.778
## 1.0 12 8 0.384 0.0801 0.2552 0.578
## 2.0 4 5 0.203 0.0736 0.0999 0.413
##
## trt=group3
## time n.risk n.event survival std.err lower 95% CI upper 95% CI
## 0.0 67 0 1.000 0.0000 1.000 1.000
## 0.5 35 28 0.565 0.0620 0.456 0.701
## 1.0 29 6 0.468 0.0628 0.360 0.609
## 2.0 21 7 0.355 0.0605 0.254 0.495## Call:
## coxph(formula = Surv(fu2y, death.or.hosp.2y) ~ trt, data = dat)
##
## n= 128, number of events= 75
##
## coef exp(coef) se(coef) z Pr(>|z|)
## trtgroup2 1.1670 3.2122 0.4854 2.404 0.0162 *
## trtgroup3 0.9581 2.6068 0.4739 2.022 0.0432 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## exp(coef) exp(-coef) lower .95 upper .95
## trtgroup2 3.212 0.3113 1.241 8.317
## trtgroup3 2.607 0.3836 1.030 6.599
##
## Concordance= 0.556 (se = 0.033 )
## Rsquare= 0.057 (max possible= 0.994 )
## Likelihood ratio test= 7.54 on 2 df, p=0.02303
## Wald test = 5.8 on 2 df, p=0.05507
## Score (logrank) test = 6.31 on 2 df, p=0.04273## Call:
## coxph(formula = Surv(fu2y, death.or.hosp.2y) ~ trt + age + bmi,
## data = dat)
##
## n= 122, number of events= 71
## (6 observations deleted due to missingness)
##
## coef exp(coef) se(coef) z Pr(>|z|)
## trtgroup2 1.137517 3.119013 0.548388 2.074 0.0381 *
## trtgroup3 0.872514 2.392919 0.534685 1.632 0.1027
## age 0.014320 1.014423 0.008971 1.596 0.1104
## bmi 0.024040 1.024331 0.016755 1.435 0.1513
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## exp(coef) exp(-coef) lower .95 upper .95
## trtgroup2 3.119 0.3206 1.0647 9.137
## trtgroup3 2.393 0.4179 0.8391 6.824
## age 1.014 0.9858 0.9967 1.032
## bmi 1.024 0.9762 0.9912 1.059
##
## Concordance= 0.62 (se = 0.037 )
## Rsquare= 0.101 (max possible= 0.993 )
## Likelihood ratio test= 13.03 on 4 df, p=0.01115
## Wald test = 10.65 on 4 df, p=0.0308
## Score (logrank) test = 11.41 on 4 df, p=0.02236## Call:
## coxph(formula = Surv(fu2y, death.or.hosp.2y) ~ trt + age + sex +
## race + bmi + diabetes, data = dat)
##
## n= 119, number of events= 69
## (9 observations deleted due to missingness)
##
## coef exp(coef) se(coef) z Pr(>|z|)
## trtgroup2 0.982208 2.670345 0.554178 1.772 0.0763 .
## trtgroup3 0.808651 2.244877 0.535009 1.511 0.1307
## age 0.005018 1.005031 0.009831 0.510 0.6097
## sexF -0.270107 0.763298 0.275601 -0.980 0.3271
## raceNon-White -0.049916 0.951309 0.270191 -0.185 0.8534
## bmi 0.021714 1.021951 0.018036 1.204 0.2286
## diabetesTRUE 0.542631 1.720527 0.262434 2.068 0.0387 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## exp(coef) exp(-coef) lower .95 upper .95
## trtgroup2 2.6703 0.3745 0.9013 7.912
## trtgroup3 2.2449 0.4455 0.7867 6.406
## age 1.0050 0.9950 0.9859 1.025
## sexF 0.7633 1.3101 0.4447 1.310
## raceNon-White 0.9513 1.0512 0.5602 1.616
## bmi 1.0220 0.9785 0.9865 1.059
## diabetesTRUE 1.7205 0.5812 1.0287 2.878
##
## Concordance= 0.623 (se = 0.037 )
## Rsquare= 0.136 (max possible= 0.993 )
## Likelihood ratio test= 17.44 on 7 df, p=0.01475
## Wald test = 15.86 on 7 df, p=0.0264
## Score (logrank) test = 16.95 on 7 df, p=0.01771Two year logistic regression
Survival by STS (yes, no)
##
## Call:
## glm(formula = death2y ~ trt, family = "binomial", data = dat)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.321 -1.296 1.040 1.040 1.701
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -1.1787 0.5718 -2.061 0.0393 *
## trtgroup2 1.4531 0.6477 2.243 0.0249 *
## trtgroup3 1.5100 0.6231 2.423 0.0154 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 176.95 on 127 degrees of freedom
## Residual deviance: 169.79 on 125 degrees of freedom
## AIC: 175.79
##
## Number of Fisher Scoring iterations: 4##
## Call:
## glm(formula = death2y ~ trt + age + bmi, family = "binomial",
## data = dat)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.6398 -1.2028 0.8159 1.0470 1.8310
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -2.55495 1.16531 -2.193 0.0283 *
## trtgroup2 1.12718 0.68637 1.642 0.1005
## trtgroup3 1.10037 0.66073 1.665 0.0958 .
## age 0.02594 0.01495 1.735 0.0828 .
## bmi 0.01062 0.02612 0.407 0.6843
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 168.60 on 121 degrees of freedom
## Residual deviance: 159.22 on 117 degrees of freedom
## (6 observations deleted due to missingness)
## AIC: 169.22
##
## Number of Fisher Scoring iterations: 4##
## Call:
## glm(formula = death2y ~ trt + age + sex + race + bmi + diabetes,
## family = "binomial", data = dat)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.8106 -1.0645 0.6786 1.0001 1.8778
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -1.376175 1.377177 -0.999 0.3177
## trtgroup2 1.078129 0.704566 1.530 0.1260
## trtgroup3 1.104863 0.676178 1.634 0.1023
## age 0.008660 0.016789 0.516 0.6060
## sexF -0.607990 0.475704 -1.278 0.2012
## raceNon-White 0.018982 0.425862 0.045 0.9644
## bmi 0.005625 0.027256 0.206 0.8365
## diabetesTRUE 0.900811 0.432934 2.081 0.0375 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 164.56 on 118 degrees of freedom
## Residual deviance: 150.41 on 111 degrees of freedom
## (9 observations deleted due to missingness)
## AIC: 166.41
##
## Number of Fisher Scoring iterations: 4Death or Hospitalization by STS (yes, no)
##
## Call:
## glm(formula = death.or.hosp.2y ~ trt, family = "binomial", data = dat)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.4671 -1.3759 0.9131 0.9911 1.5645
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -0.8755 0.5323 -1.645 0.1000
## trtgroup2 1.5347 0.6201 2.475 0.0133 *
## trtgroup3 1.3309 0.5884 2.262 0.0237 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 173.65 on 127 degrees of freedom
## Residual deviance: 166.56 on 125 degrees of freedom
## AIC: 172.56
##
## Number of Fisher Scoring iterations: 4##
## Call:
## glm(formula = death.or.hosp.2y ~ trt + age + bmi, family = "binomial",
## data = dat)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.8036 -1.2486 0.7812 0.9694 1.8491
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -2.75715 1.19132 -2.314 0.0206 *
## trtgroup2 1.54399 0.69292 2.228 0.0259 *
## trtgroup3 1.20141 0.66160 1.816 0.0694 .
## age 0.02455 0.01534 1.600 0.1096
## bmi 0.01982 0.02689 0.737 0.4610
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 165.83 on 121 degrees of freedom
## Residual deviance: 153.70 on 117 degrees of freedom
## (6 observations deleted due to missingness)
## AIC: 163.7
##
## Number of Fisher Scoring iterations: 4##
## Call:
## glm(formula = death.or.hosp.2y ~ trt + age + sex + race + bmi +
## diabetes, family = "binomial", data = dat)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.1508 -1.0489 0.4629 0.8814 1.9785
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -0.9095707 1.4449622 -0.629 0.5290
## trtgroup2 1.6231725 0.7298096 2.224 0.0261 *
## trtgroup3 1.2808245 0.6946819 1.844 0.0652 .
## age -0.0002247 0.0176506 -0.013 0.9898
## sexF -1.3021440 0.5411694 -2.406 0.0161 *
## raceNon-White 0.0199006 0.4449487 0.045 0.9643
## bmi 0.0184373 0.0281639 0.655 0.5127
## diabetesTRUE 1.1535334 0.4713908 2.447 0.0144 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 161.92 on 118 degrees of freedom
## Residual deviance: 138.74 on 111 degrees of freedom
## (9 observations deleted due to missingness)
## AIC: 154.74
##
## Number of Fisher Scoring iterations: 4