respiratory.RdThe data are from a clinical trial of patients with respiratory illness, where 111 patients from two different clinics were randomized to receive either placebo or an active treatment. Patients were examined at baseline and at four visits during treatment. The respiratory status (categorized as 1 = good, 0 = poor) was determined at each visit.
respiratoryA data frame with 444 observations on the following 8 variables.
a numeric vector
a numeric vector
treatment or placebo
M or F
in years at baseline
resporatory status at baseline
id of each of four visits
respiratory status at each visit
data(respiratory)
data(respiratory, package="geepack")
respiratory$center <- factor(respiratory$center)
head(respiratory)
#> center id treat sex age baseline visit outcome
#> 1 1 1 P M 46 0 1 0
#> 2 1 1 P M 46 0 2 0
#> 3 1 1 P M 46 0 3 0
#> 4 1 1 P M 46 0 4 0
#> 5 1 2 P M 28 0 1 0
#> 6 1 2 P M 28 0 2 0
m1 <- glm(outcome ~ center + treat + age + baseline, data=respiratory,
family=binomial())
gee.ind <- geeglm(outcome ~ center + treat + age + baseline, data=respiratory, id=id,
family=binomial(), corstr="independence")
gee.exc <- geeglm(outcome ~ center + treat + age + baseline, data=respiratory, id=id,
family=binomial(), corstr="exchangeable")
gee.uns <- geeglm(outcome ~ center + treat + age + baseline, data=respiratory, id=id,
family=binomial(), corstr="unstructured")
gee.ar1 <- geeglm(outcome ~ center + treat + age + baseline, data=respiratory, id=id,
family=binomial(), corstr="ar1")
mlist <- list(gee.ind, gee.exc, gee.uns, gee.ar1)
do.call(rbind, lapply(mlist, QIC))
#> QIC QICu Quasi Lik CIC params QICC
#> [1,] 531.2 497.7 -243.9 21.74 5 532.4
#> [2,] 531.2 497.7 -243.9 21.74 5 532.9
#> [3,] 531.0 497.8 -243.9 21.61 5 537.0
#> [4,] 531.7 498.1 -244.0 21.79 5 533.4
lapply(mlist, tidy)
#> [[1]]
#> # A tibble: 5 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept) 0.389 0.449 0.750 0.387
#> 2 center2 0.669 0.340 3.88 0.0490
#> 3 treatP -1.24 0.324 14.7 0.000127
#> 4 age -0.0178 0.0120 2.20 0.138
#> 5 baseline 1.83 0.337 29.6 0.0000000544
#>
#> [[2]]
#> # A tibble: 5 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept) 0.389 0.449 0.750 0.387
#> 2 center2 0.669 0.340 3.88 0.0490
#> 3 treatP -1.24 0.324 14.7 0.000127
#> 4 age -0.0178 0.0120 2.20 0.138
#> 5 baseline 1.83 0.337 29.6 0.0000000544
#>
#> [[3]]
#> # A tibble: 5 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept) 0.341 0.444 0.590 0.442
#> 2 center2 0.672 0.339 3.93 0.0475
#> 3 treatP -1.22 0.323 14.3 0.000154
#> 4 age -0.0168 0.0119 1.99 0.159
#> 5 baseline 1.89 0.335 31.8 0.0000000175
#>
#> [[4]]
#> # A tibble: 5 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept) 0.252 0.445 0.322 0.570
#> 2 center2 0.749 0.341 4.81 0.0282
#> 3 treatP -1.17 0.326 12.8 0.000344
#> 4 age -0.0165 0.0119 1.90 0.168
#> 5 baseline 1.86 0.337 30.4 0.0000000360
#>