## Error: could not find function "libraary"
## degree
## 0 1 2 3 4 7
## 33694 2614 5216 523 1347 959
## diploma
## 0 1 2 3 4 5 6 7 8 9 10 11
## 19989 4145 517 1810 795 1789 3038 1146 2159 487 889 1
## 12 13 14 15 17 20 37
## 701 1701 452 2105 496 1446 687
ICU and Hospital mortality
display(cost.icu <- lmer(diedicu ~ IMlo + prop.occ.c + mean.daily.transfer +
N.dc.quart * ave.cost.nurse + N.supernum.perbed + num.consult.perbed + intensivist +
IMlomean.x + I(avyulos/100) + (1 | trust.code), data = dta4, family = binomial(),
na.action = na.omit, subset = ss8), digits = 3)
## glmer(formula = diedicu ~ IMlo + prop.occ.c + mean.daily.transfer +
## N.dc.quart * ave.cost.nurse + N.supernum.perbed + num.consult.perbed +
## intensivist + IMlomean.x + I(avyulos/100) + (1 | trust.code),
## data = dta4, family = binomial(), subset = ss8, na.action = na.omit)
## coef.est coef.se
## (Intercept) -2.045 0.410
## IMlo 0.966 0.012
## prop.occ.c 0.253 0.096
## mean.daily.transfer 0.488 0.409
## N.dc.quart(4.25,4.82] -1.063 1.118
## N.dc.quart(4.82,5.68] 0.043 0.567
## N.dc.quart(5.68,14.2] -0.372 1.022
## ave.cost.nurse 0.019 0.017
## N.supernum.perbed 0.034 0.099
## num.consult.perbed -0.327 0.106
## intensivistYes -0.146 0.113
## IMlomean.x -0.053 0.020
## I(avyulos/100) 0.403 0.154
## N.dc.quart(4.25,4.82]:ave.cost.nurse 0.052 0.053
## N.dc.quart(4.82,5.68]:ave.cost.nurse -0.005 0.025
## N.dc.quart(5.68,14.2]:ave.cost.nurse 0.011 0.050
##
## Error terms:
## Groups Name Std.Dev.
## trust.code (Intercept) 0.285
## Residual 1.000
## ---
## number of obs: 36935, groups: trust.code, 63
## AIC = 22546.4, DIC = 22512
## deviance = 22512.4
display(cost.hosp <- lmer(diedhosp ~ IMlo + prop.occ.c + mean.daily.transfer +
N.dc.quart * ave.cost.nurse + N.supernum.perbed + num.consult.perbed + intensivist +
IMlomean.x + I(avyulos/100) + (1 | trust.code), data = dta4, family = binomial(),
na.action = na.omit, subset = ss8), digits = 3)
## glmer(formula = diedhosp ~ IMlo + prop.occ.c + mean.daily.transfer +
## N.dc.quart * ave.cost.nurse + N.supernum.perbed + num.consult.perbed +
## intensivist + IMlomean.x + I(avyulos/100) + (1 | trust.code),
## data = dta4, family = binomial(), subset = ss8, na.action = na.omit)
## coef.est coef.se
## (Intercept) -0.498 0.373
## IMlo 0.960 0.011
## prop.occ.c 0.245 0.082
## mean.daily.transfer 0.932 0.377
## N.dc.quart(4.25,4.82] 0.151 1.019
## N.dc.quart(4.82,5.68] 0.004 0.498
## N.dc.quart(5.68,14.2] 0.450 0.886
## ave.cost.nurse 0.001 0.015
## N.supernum.perbed 0.027 0.090
## num.consult.perbed -0.239 0.095
## intensivistYes -0.124 0.103
## IMlomean.x -0.042 0.017
## I(avyulos/100) 0.247 0.140
## N.dc.quart(4.25,4.82]:ave.cost.nurse -0.006 0.048
## N.dc.quart(4.82,5.68]:ave.cost.nurse -0.002 0.022
## N.dc.quart(5.68,14.2]:ave.cost.nurse -0.030 0.043
##
## Error terms:
## Groups Name Std.Dev.
## trust.code (Intercept) 0.267
## Residual 1.000
## ---
## number of obs: 36359, groups: trust.code, 63
## AIC = 29335, DIC = 29301
## deviance = 29301.0
display(pbq.icu <- lmer(diedicu ~ IMlo + prop.occ.c + mean.daily.transfer +
N.dc.quart * ratio.pbq.wte + N.supernum.perbed + num.consult.perbed + intensivist +
IMlomean.x + I(avyulos/100) + (1 | trust.code), data = dta4, family = binomial(),
na.action = na.omit, subset = ss8), digits = 3)
## glmer(formula = diedicu ~ IMlo + prop.occ.c + mean.daily.transfer +
## N.dc.quart * ratio.pbq.wte + N.supernum.perbed + num.consult.perbed +
## intensivist + IMlomean.x + I(avyulos/100) + (1 | trust.code),
## data = dta4, family = binomial(), subset = ss8, na.action = na.omit)
## coef.est coef.se
## (Intercept) -0.833 0.291
## IMlo 0.965 0.012
## prop.occ.c 0.229 0.094
## mean.daily.transfer 0.725 0.336
## N.dc.quart(4.25,4.82] -0.641 0.285
## N.dc.quart(4.82,5.68] -0.919 0.296
## N.dc.quart(5.68,14.2] -1.059 0.274
## ratio.pbq.wte -0.974 0.283
## N.supernum.perbed 0.014 0.086
## num.consult.perbed -0.301 0.090
## intensivistYes -0.192 0.100
## IMlomean.x -0.051 0.020
## I(avyulos/100) 0.362 0.138
## N.dc.quart(4.25,4.82]:ratio.pbq.wte 0.827 0.350
## N.dc.quart(4.82,5.68]:ratio.pbq.wte 1.075 0.372
## N.dc.quart(5.68,14.2]:ratio.pbq.wte 1.182 0.359
##
## Error terms:
## Groups Name Std.Dev.
## trust.code (Intercept) 0.249
## Residual 1.000
## ---
## number of obs: 38168, groups: trust.code, 65
## AIC = 23318.4, DIC = 23284
## deviance = 23284.4
display(pbq.hosp <- lmer(diedhosp ~ IMlo + prop.occ.c + mean.daily.transfer +
N.dc.quart * ratio.pbq.wte + N.supernum.perbed + num.consult.perbed + intensivist +
IMlomean.x + I(avyulos/100) + (1 | trust.code), data = dta4, family = binomial(),
na.action = na.omit, subset = ss8), digits = 3)
## glmer(formula = diedhosp ~ IMlo + prop.occ.c + mean.daily.transfer +
## N.dc.quart * ratio.pbq.wte + N.supernum.perbed + num.consult.perbed +
## intensivist + IMlomean.x + I(avyulos/100) + (1 | trust.code),
## data = dta4, family = binomial(), subset = ss8, na.action = na.omit)
## coef.est coef.se
## (Intercept) -0.160 0.277
## IMlo 0.961 0.011
## prop.occ.c 0.208 0.080
## mean.daily.transfer 0.857 0.330
## N.dc.quart(4.25,4.82] -0.051 0.274
## N.dc.quart(4.82,5.68] -0.421 0.284
## N.dc.quart(5.68,14.2] -0.387 0.263
## ratio.pbq.wte -0.344 0.271
## N.supernum.perbed -0.001 0.082
## num.consult.perbed -0.243 0.085
## intensivistYes -0.127 0.096
## IMlomean.x -0.042 0.017
## I(avyulos/100) 0.250 0.132
## N.dc.quart(4.25,4.82]:ratio.pbq.wte 0.091 0.335
## N.dc.quart(4.82,5.68]:ratio.pbq.wte 0.509 0.355
## N.dc.quart(5.68,14.2]:ratio.pbq.wte 0.323 0.342
##
## Error terms:
## Groups Name Std.Dev.
## trust.code (Intercept) 0.250
## Residual 1.000
## ---
## number of obs: 37590, groups: trust.code, 65
## AIC = 30371.1, DIC = 30337
## deviance = 30337.1
ef.cost.icu <- effect("N.dc.quart:ave.cost.nurse", cost.icu)
ef.cost.hosp <- effect("N.dc.quart:ave.cost.nurse", cost.hosp)
ef.pbq.icu <- effect("N.dc.quart:ratio.pbq.wte", pbq.icu)
ef.pbq.hosp <- effect("N.dc.quart:ratio.pbq.wte", pbq.hosp)
plot(ef.pbq.icu)
display(ot.icu <- lmer(diedicu ~ IMlo + prop.occ.c + mean.daily.transfer + N.dc.quart *
ratio.ot.total.spend + N.supernum.perbed + num.consult.perbed + intensivist +
IMlomean.x + I(avyulos/100) + (1 | trust.code), data = dta4, family = binomial(),
na.action = na.omit, subset = ss8), digits = 3)
## glmer(formula = diedicu ~ IMlo + prop.occ.c + mean.daily.transfer +
## N.dc.quart * ratio.ot.total.spend + N.supernum.perbed + num.consult.perbed +
## intensivist + IMlomean.x + I(avyulos/100) + (1 | trust.code),
## data = dta4, family = binomial(), subset = ss8, na.action = na.omit)
## coef.est coef.se
## (Intercept) -1.693 0.204
## IMlo 0.965 0.012
## prop.occ.c 0.261 0.096
## mean.daily.transfer 0.789 0.370
## N.dc.quart(4.25,4.82] -0.084 0.122
## N.dc.quart(4.82,5.68] -0.134 0.116
## N.dc.quart(5.68,14.2] -0.165 0.118
## ratio.ot.total.spend -1.962 7.041
## N.supernum.perbed 0.020 0.095
## num.consult.perbed -0.244 0.099
## intensivistYes -0.183 0.112
## IMlomean.x -0.055 0.020
## I(avyulos/100) 0.423 0.152
## N.dc.quart(4.25,4.82]:ratio.ot.total.spend 14.977 11.803
## N.dc.quart(4.82,5.68]:ratio.ot.total.spend 9.708 11.314
## N.dc.quart(5.68,14.2]:ratio.ot.total.spend -1.343 10.841
##
## Error terms:
## Groups Name Std.Dev.
## trust.code (Intercept) 0.275
## Residual 1.000
## ---
## number of obs: 36935, groups: trust.code, 63
## AIC = 22545.2, DIC = 22511
## deviance = 22511.2
display(ot.hosp <- lmer(diedhosp ~ IMlo + prop.occ.c + mean.daily.transfer +
N.dc.quart * ratio.ot.total.spend + N.supernum.perbed + num.consult.perbed +
intensivist + IMlomean.x + I(avyulos/100) + (1 | trust.code), data = dta4,
family = binomial(), na.action = na.omit, subset = ss8), digits = 3)
## glmer(formula = diedhosp ~ IMlo + prop.occ.c + mean.daily.transfer +
## N.dc.quart * ratio.ot.total.spend + N.supernum.perbed + num.consult.perbed +
## intensivist + IMlomean.x + I(avyulos/100) + (1 | trust.code),
## data = dta4, family = binomial(), subset = ss8, na.action = na.omit)
## coef.est coef.se
## (Intercept) -0.540 0.181
## IMlo 0.960 0.011
## prop.occ.c 0.246 0.082
## mean.daily.transfer 1.005 0.334
## N.dc.quart(4.25,4.82] -0.096 0.109
## N.dc.quart(4.82,5.68] -0.081 0.102
## N.dc.quart(5.68,14.2] -0.138 0.105
## ratio.ot.total.spend -2.345 6.362
## N.supernum.perbed -0.001 0.086
## num.consult.perbed -0.205 0.088
## intensivistYes -0.192 0.100
## IMlomean.x -0.041 0.017
## I(avyulos/100) 0.327 0.136
## N.dc.quart(4.25,4.82]:ratio.ot.total.spend 25.442 10.424
## N.dc.quart(4.82,5.68]:ratio.ot.total.spend 9.131 10.180
## N.dc.quart(5.68,14.2]:ratio.ot.total.spend 8.603 9.609
##
## Error terms:
## Groups Name Std.Dev.
## trust.code (Intercept) 0.250
## Residual 1.000
## ---
## number of obs: 36359, groups: trust.code, 63
## AIC = 29326.7, DIC = 29293
## deviance = 29292.7
### Effect plo t
ef.ot.icu <- effect("N.dc.quart:ratio.ot.total.spend", ot.icu)
ef.ot.hosp <- effect("N.dc.quart:ratio.ot.total.spend", ot.hosp)
plot(ef.ot.icu)
plot(ef.ot.hosp)
display(bank.icu <- lmer(diedicu ~ IMlo + prop.occ.c + mean.daily.transfer +
N.dc.quart * ratio.bank.total.spend + N.supernum.perbed + num.consult.perbed +
intensivist + IMlomean.x + I(avyulos/100) + (1 | trust.code), data = dta4,
family = binomial(), na.action = na.omit, subset = ss8), digits = 3)
## glmer(formula = diedicu ~ IMlo + prop.occ.c + mean.daily.transfer +
## N.dc.quart * ratio.bank.total.spend + N.supernum.perbed +
## num.consult.perbed + intensivist + IMlomean.x + I(avyulos/100) +
## (1 | trust.code), data = dta4, family = binomial(), subset = ss8,
## na.action = na.omit)
## coef.est coef.se
## (Intercept) -1.688 0.199
## IMlo 0.966 0.012
## prop.occ.c 0.270 0.096
## mean.daily.transfer 1.070 0.405
## N.dc.quart(4.25,4.82] 0.089 0.133
## N.dc.quart(4.82,5.68] -0.075 0.129
## N.dc.quart(5.68,14.2] -0.249 0.137
## ratio.bank.total.spend 1.197 4.249
## N.supernum.perbed 0.007 0.101
## num.consult.perbed -0.264 0.097
## intensivistYes -0.137 0.108
## IMlomean.x -0.054 0.020
## I(avyulos/100) 0.382 0.159
## N.dc.quart(4.25,4.82]:ratio.bank.total.spend -5.031 4.755
## N.dc.quart(4.82,5.68]:ratio.bank.total.spend -2.113 4.583
## N.dc.quart(5.68,14.2]:ratio.bank.total.spend 0.257 4.561
##
## Error terms:
## Groups Name Std.Dev.
## trust.code (Intercept) 0.279
## Residual 1.000
## ---
## number of obs: 36935, groups: trust.code, 63
## AIC = 22545.6, DIC = 22512
## deviance = 22511.6
display(bank.hosp <- lmer(diedhosp ~ IMlo + prop.occ.c + mean.daily.transfer +
N.dc.quart * ratio.bank.total.spend + N.supernum.perbed + num.consult.perbed +
intensivist + IMlomean.x + I(avyulos/100) + (1 | trust.code), data = dta4,
family = binomial(), na.action = na.omit, subset = ss8), digits = 3)
## glmer(formula = diedhosp ~ IMlo + prop.occ.c + mean.daily.transfer +
## N.dc.quart * ratio.bank.total.spend + N.supernum.perbed +
## num.consult.perbed + intensivist + IMlomean.x + I(avyulos/100) +
## (1 | trust.code), data = dta4, family = binomial(), subset = ss8,
## na.action = na.omit)
## coef.est coef.se
## (Intercept) -0.555 0.172
## IMlo 0.960 0.011
## prop.occ.c 0.250 0.082
## mean.daily.transfer 1.250 0.350
## N.dc.quart(4.25,4.82] 0.179 0.114
## N.dc.quart(4.82,5.68] -0.006 0.111
## N.dc.quart(5.68,14.2] -0.087 0.117
## ratio.bank.total.spend 4.054 3.690
## N.supernum.perbed -0.032 0.088
## num.consult.perbed -0.222 0.084
## intensivistYes -0.095 0.093
## IMlomean.x -0.042 0.017
## I(avyulos/100) 0.282 0.138
## N.dc.quart(4.25,4.82]:ratio.bank.total.spend -9.396 4.126
## N.dc.quart(4.82,5.68]:ratio.bank.total.spend -4.654 3.979
## N.dc.quart(5.68,14.2]:ratio.bank.total.spend -5.084 3.956
##
## Error terms:
## Groups Name Std.Dev.
## trust.code (Intercept) 0.243
## Residual 1.000
## ---
## number of obs: 36359, groups: trust.code, 63
## AIC = 29326.4, DIC = 29292
## deviance = 29292.4
ef.bank.icu <- effect("N.dc.quart:ratio.bank.total.spend", bank.icu)
ef.bank.hosp <- effect("N.dc.quart:ratio.bank.total.spend", bank.hosp)
plot(ef.bank.icu)
plot(ef.bank.hosp)
