Last updated on 2025-05-18 08:50:55 CEST.
| Package | ERROR | NOTE | OK |
|---|---|---|---|
| pec | 6 | 7 | |
| prodlim | 13 | ||
| Publish | 6 | 7 | |
| riskRegression | 1 | 4 | 8 |
| SmoothHazard | 6 | 7 |
Current CRAN status: NOTE: 6, OK: 7
Version: 2023.04.12
Check: CRAN incoming feasibility
Result: NOTE
Maintainer: ‘Thomas A. Gerds <tag@biostat.ku.dk>’
No Authors@R field in DESCRIPTION.
Please add one, modifying
Authors@R: person(given = c("Thomas", "A."),
family = "Gerds",
role = c("aut", "cre"),
email = "tag@biostat.ku.dk")
as necessary.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Version: 2023.04.12
Check: Rd cross-references
Result: NOTE
Found the following Rd file(s) with Rd \link{} targets missing package
anchors:
calPlot.Rd: SmartControl, dpik
coxboost.Rd: Hist
plot.pec.Rd: prodlim
plotPredictEventProb.Rd: SmartControl, prodlim
plotPredictSurvProb.Rd: SmartControl, prodlim
predictRestrictedMeanTime.Rd: survfit
predictSurvProb.Rd: survfit
selectCox.Rd: fastbw
Please provide package anchors for all Rd \link{} targets not in the
package itself and the base packages.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-windows-x86_64, r-patched-linux-x86_64, r-release-linux-x86_64, r-release-windows-x86_64
Current CRAN status: OK: 13
Current CRAN status: NOTE: 6, OK: 7
Version: 2023.01.17
Check: Rd cross-references
Result: NOTE
Found the following Rd file(s) with Rd \link{} targets missing package
anchors:
followupTable.Rd: anova.coxph
specialFrame.Rd: model.design, strata, strip.terms
stripes.Rd: plot.prodlim
Please provide package anchors for all Rd \link{} targets not in the
package itself and the base packages.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-windows-x86_64, r-patched-linux-x86_64, r-release-linux-x86_64, r-release-windows-x86_64
Current CRAN status: ERROR: 1, NOTE: 4, OK: 8
Version: 2023.12.21
Check: Rd cross-references
Result: NOTE
Found the following Rd file(s) with Rd \link{} targets missing package
anchors:
CSC.Rd: coxph
FGR.Rd: Hist
ate.Rd: as.data.table
plot.riskRegression.Rd: SmartControl
plotBrier.Rd: SmartControl
plotCalibration.Rd: SmartControl
plotEffects.Rd: SmartControl
plotPredictRisk.Rd: SmartControl
plotROC.Rd: SmartControl
plotRisk.Rd: SmartControl
selectCox.Rd: fastbw
summary.ate.Rd: as.data.table
Please provide package anchors for all Rd \link{} targets not in the
package itself and the base packages.
Flavors: r-devel-linux-x86_64-debian-clang, r-patched-linux-x86_64
Version: 2025.05.15
Check: examples
Result: ERROR
Running examples in 'riskRegression-Ex.R' failed
The error most likely occurred in:
> ### Name: wglm
> ### Title: Logistic Regression Using IPCW
> ### Aliases: wglm
>
> ### ** Examples
>
> library(survival)
>
> #### simulate data ####
> set.seed(10)
> n <- 250
> tau <- 1:5
> d <- sampleData(n, outcome = "competing.risks")
> dFull <- d[event!=0] ## (artificially) remove censoring
> dSurv <- d[event!=2] ## (artificially) remove competing risk
>
> #### no censoring ####
> e.wglm <- wglm(Surv(time,event) ~ X1,
+ times = tau, data = dFull, product.limit = TRUE)
> e.wglm ## same as a logistic regression at each timepoint
logistic regression for cause 1
- structure: Surv(time, event) with possible states: 0, 1, 2.
- outcome model: ~X1 (fitter: glm function).
- estimated regression parameters:
n.censor n.event IPCW(max) (Intercept) X11
1 0 17 1 -2.4298469 1.2258741
2 0 39 1 -1.3719056 0.5609754
3 0 58 1 -0.8445468 0.6903961
4 0 73 1 -0.4831741 0.6373248
5 0 89 1 -0.1505729 0.9615031
>
> coef(e.wglm)
(Intercept) X11
1 -2.4298469 1.2258741
2 -1.3719056 0.5609754
3 -0.8445468 0.6903961
4 -0.4831741 0.6373248
5 -0.1505729 0.9615031
> confint(e.wglm)
estimate lower upper
(Intercept)(t=1) -2.4298469 -2.9762442 -1.8834496
X11(t=1) 1.2258741 -0.1752620 2.6270101
(Intercept)(t=2) -1.3719056 -1.7428404 -1.0009708
X11(t=2) 0.5609754 -0.6738469 1.7957977
(Intercept)(t=3) -0.8445468 -1.1695419 -0.5195517
X11(t=3) 0.6903961 -0.4474284 1.8282207
(Intercept)(t=4) -0.4831741 -0.7899401 -0.1764080
X11(t=4) 0.6373248 -0.4954278 1.7700773
(Intercept)(t=5) -0.1505729 -0.4494445 0.1482988
X11(t=5) 0.9615031 -0.2536174 2.1766235
> model.tables(e.wglm)
name time estimate se statistic lower upper
1 (Intercept) 1 -2.4298469 0.2787793 -8.7160243 -2.9762442 -1.8834496
2 X11 1 1.2258741 0.7148785 1.7148007 -0.1752620 2.6270101
3 (Intercept) 2 -1.3719056 0.1892559 -7.2489441 -1.7428404 -1.0009708
4 X11 2 0.5609754 0.6300229 0.8904047 -0.6738469 1.7957977
5 (Intercept) 3 -0.8445468 0.1658169 -5.0932505 -1.1695419 -0.5195517
6 X11 3 0.6903961 0.5805334 1.1892445 -0.4474284 1.8282207
7 (Intercept) 4 -0.4831741 0.1565162 -3.0870556 -0.7899401 -0.1764080
8 X11 4 0.6373248 0.5779456 1.1027418 -0.4954278 1.7700773
9 (Intercept) 5 -0.1505729 0.1524883 -0.9874386 -0.4494445 0.1482988
10 X11 5 0.9615031 0.6199708 1.5508844 -0.2536174 2.1766235
p.value
1 0.000000e+00
2 8.638178e-02
3 4.201084e-13
4 3.732486e-01
5 3.519761e-07
6 2.343435e-01
7 2.021498e-03
8 2.701393e-01
9 3.234277e-01
10 1.209294e-01
>
> summary(ate(e.wglm, data = dFull, times = tau, treatment = "X1", verbose = FALSE))
Average treatment effect for cause 1
- Treatment : X1 (2 levels: "0" "1")
- Event : event (cause: 1, competing risk(s): 0 2)
- Time [min;max] : time [0.136;13.9]
- at risk/time : 1 2 3 4 5
number in treatment 0 151 126 98 74 52
number in treatment 1 10 9 7 4 2
Estimation procedure
- Estimator : G-formula
- Uncertainty: Gaussian approximation
where the variance is estimated via the influence function
Testing procedure
- Null hypothesis : given two treatments (A,B) and a specific timepoint, equal risks
- Confidence level : 0.95
Results:
- Difference in standardized risk (B-A) between time zero and 'time'
reported on the scale [-1;1] (difference between two probabilities)
(difference in average risks when treating all subjects with the experimental treatment (B),
vs. treating all subjects with the reference treatment (A))
time X1=A risk(X1=A) X1=B risk(X1=B) difference ci p.value
1 0 0.0809 1 0.231 0.150 [-0.08;0.38] 0.2067
2 0 0.2023 1 0.308 0.105 [-0.15;0.36] 0.4233
3 0 0.3006 1 0.462 0.161 [-0.12;0.44] 0.2590
4 0 0.3815 1 0.538 0.157 [-0.12;0.44] 0.2727
5 0 0.4624 1 0.692 0.230 [-0.03;0.49] 0.0851
difference : estimated difference in standardized risks
ci : pointwise confidence intervals
p.value : (unadjusted) p-value
> #### right-censoring ####
> ## no covariante in the censoring model (independent censoring)
> eC.wglm <- wglm(Surv(time,event) ~ X1,
+ times = tau, data = dSurv, product.limit = TRUE)
> summary(eC.wglm)
IPCW logistic regression for cause 1
- structure: Surv(time, event) with possible states: 0, 1.
- censoring model: ~1 (fitter: prodlim function).
- outcome model: ~X1 (fitter: glm function).
- estimated regression parameters:
------ time: 1 ----------------------------------------------
- number (events, no event, censoring): 17, 157, 1
- IPCW (min,median,max): 1, 1.00595, 1.00595
Estimate Std. Error z value Pr(>|z|)
(Intercept) -2.360270 0.2796095 -8.441311 0.00000000
X11 1.259684 0.7229336 1.742461 0.08142774
------ time: 2 ----------------------------------------------
- number (events, no event, censoring): 39, 131, 5
- IPCW (min,median,max): 1, 1.03433, 1.03433
Estimate Std. Error z value Pr(>|z|)
(Intercept) -1.2773875 0.1913028 -6.6773078 2.433720e-11
X11 0.5600438 0.6416583 0.8728069 3.827683e-01
------ time: 3 ----------------------------------------------
- number (events, no event, censoring): 58, 106, 11
- IPCW (min,median,max): 1, 1.08774, 1.08774
Estimate Std. Error z value Pr(>|z|)
(Intercept) -0.7089823 0.1700057 -4.170346 3.041381e-05
X11 0.6522529 0.6022446 1.083036 2.787922e-01
------ time: 4 ----------------------------------------------
- number (events, no event, censoring): 73, 80, 22
- IPCW (min,median,max): 1, 1.22925, 1.22925
Estimate Std. Error z value Pr(>|z|)
(Intercept) -0.2974887 0.1642070 -1.811669 0.07003737
X11 0.6894027 0.6491468 1.062014 0.28822952
------ time: 5 ----------------------------------------------
- number (events, no event, censoring): 89, 55, 31
- IPCW (min,median,max): 1, 1.20033, 1.40226
Estimate Std. Error z value Pr(>|z|)
(Intercept) 0.1487129 0.1695233 0.8772414 0.3803555
X11 1.8170644 1.0695995 1.6988269 0.0893518
>
> weights(eC.wglm)
t1 t2 t3 t4 t5
1 1.005952 1.034325 1.087743 1.229252 1.402257
2 1.005952 1.034325 1.087743 1.229252 1.402257
3 1.000000 1.000000 1.000000 1.000000 1.000000
4 1.005952 1.034325 1.087743 1.229252 1.334264
5 1.005952 1.034325 1.050551 1.050551 1.050551
6 1.005952 1.034325 1.087743 1.229252 1.402257
7 1.005952 1.005952 1.005952 1.005952 1.005952
8 1.005952 1.034325 1.087743 1.229252 1.402257
9 1.005952 1.034325 1.068207 1.068207 1.068207
10 1.005952 1.034325 1.087743 1.229252 1.402257
11 1.005952 1.034325 1.087743 1.229252 1.402257
12 1.005952 1.005952 1.005952 1.005952 1.005952
13 1.005952 1.034325 1.050551 1.050551 1.050551
14 1.005952 1.034325 1.068207 1.068207 1.068207
15 1.005952 1.034325 1.087743 1.229252 1.402257
16 1.005952 1.034325 1.087743 1.229252 1.244812
17 1.005952 1.034325 1.087743 1.229252 0.000000
18 1.005952 1.026489 1.026489 1.026489 1.026489
19 1.005952 1.005952 1.005952 1.005952 1.005952
20 1.005952 1.034325 1.087743 1.171405 1.171405
21 1.005952 1.034325 1.087743 1.229252 1.402257
22 1.005952 1.034325 1.087743 1.087743 1.087743
23 1.005952 1.005952 1.005952 1.005952 1.005952
24 1.005952 1.034325 0.000000 0.000000 0.000000
25 1.005952 1.034325 1.087743 1.229252 1.402257
26 1.005952 1.034325 1.087743 1.087743 1.087743
27 1.005952 1.034325 1.042343 1.042343 1.042343
28 1.005952 1.019459 1.019459 1.019459 1.019459
29 1.000000 1.000000 1.000000 1.000000 1.000000
30 1.005952 1.034325 1.087743 1.229252 1.402257
31 1.005952 1.034325 1.087743 1.229252 1.402257
32 1.005952 1.034325 1.077577 1.077577 1.077577
33 1.005952 1.012570 1.012570 1.012570 1.012570
34 1.005952 1.034325 0.000000 0.000000 0.000000
35 1.005952 1.034325 1.087743 1.229252 1.402257
36 1.005952 1.034325 1.087743 1.229252 1.334264
37 1.005952 1.026489 1.026489 1.026489 1.026489
38 1.005952 1.034325 1.087743 1.229252 1.402257
39 1.005952 1.034325 1.087743 1.229252 1.402257
40 1.005952 1.034325 1.087743 1.229252 1.402257
41 1.005952 1.034325 1.077577 1.077577 1.077577
42 1.005952 1.034325 1.087743 1.229252 1.402257
43 1.005952 1.034325 1.050551 1.050551 1.050551
44 1.005952 1.012570 1.012570 1.012570 1.012570
45 1.005952 1.034325 1.087743 1.229252 1.402257
46 1.005952 1.034325 1.087743 1.229252 1.402257
47 1.005952 1.034325 1.087743 1.229252 1.402257
48 1.005952 1.034325 1.087743 1.229252 1.402257
49 1.000000 1.000000 1.000000 1.000000 1.000000
50 1.005952 1.034325 1.087743 1.229252 1.244812
51 1.005952 1.034325 1.087743 1.229252 1.402257
52 1.005952 1.034325 1.087743 1.229252 1.402257
53 1.005952 1.034325 1.050551 1.050551 1.050551
54 1.005952 0.000000 0.000000 0.000000 0.000000
55 1.005952 1.005952 1.005952 1.005952 1.005952
56 1.005952 1.005952 1.005952 1.005952 1.005952
57 1.005952 1.034325 1.087743 1.229252 1.402257
58 1.005952 1.012570 1.012570 1.012570 1.012570
59 1.005952 1.034325 1.087743 1.229252 1.402257
60 1.005952 1.034325 1.087743 1.087743 1.087743
61 1.005952 1.034325 1.087743 1.229252 1.402257
62 1.005952 1.034325 1.050551 1.050551 1.050551
63 1.005952 1.034325 1.087743 1.229252 0.000000
64 1.005952 1.026489 1.026489 1.026489 1.026489
65 1.005952 1.034325 1.087743 1.229252 1.402257
66 1.005952 1.005952 1.005952 1.005952 1.005952
67 1.005952 1.034325 1.068207 1.068207 1.068207
68 1.005952 1.034325 0.000000 0.000000 0.000000
69 1.005952 1.034325 1.087743 0.000000 0.000000
70 1.005952 0.000000 0.000000 0.000000 0.000000
71 1.005952 1.034325 1.077577 1.077577 1.077577
72 1.005952 1.005952 1.005952 1.005952 1.005952
73 1.005952 1.034325 1.087743 1.229252 0.000000
74 1.005952 1.034325 1.087743 1.109718 1.109718
75 1.005952 1.026489 1.026489 1.026489 1.026489
76 1.005952 1.005952 1.005952 1.005952 1.005952
77 1.005952 1.034325 1.087743 1.229252 1.244812
78 1.005952 1.026489 1.026489 1.026489 1.026489
79 1.005952 1.026489 1.026489 1.026489 1.026489
80 1.005952 1.034325 1.087743 1.229252 0.000000
81 1.005952 1.034325 1.087743 1.145515 1.145515
82 1.005952 1.005952 1.005952 1.005952 1.005952
83 1.005952 1.034325 1.087743 1.229252 1.402257
84 1.005952 1.034325 1.068207 1.068207 1.068207
85 1.005952 1.034325 1.087743 1.229252 1.402257
86 1.005952 1.026489 1.026489 1.026489 1.026489
87 1.005952 1.034325 1.087743 1.229252 1.378080
88 1.005952 1.034325 1.087743 0.000000 0.000000
89 1.005952 1.034325 0.000000 0.000000 0.000000
90 1.005952 1.034325 1.087743 0.000000 0.000000
91 1.000000 1.000000 1.000000 1.000000 1.000000
92 1.005952 1.034325 1.087743 1.229252 1.355112
93 1.005952 1.034325 1.087743 1.109718 1.109718
94 1.005952 1.034325 1.087743 0.000000 0.000000
95 1.005952 1.005952 1.005952 1.005952 1.005952
96 1.005952 1.026489 1.026489 1.026489 1.026489
97 1.005952 1.034325 1.087743 1.229252 1.402257
98 1.005952 1.034325 1.087743 1.229252 1.402257
99 1.005952 1.034325 1.087743 1.229252 1.402257
100 1.005952 1.034325 0.000000 0.000000 0.000000
101 1.005952 1.034325 1.087743 1.229252 1.402257
102 1.005952 1.034325 1.087743 1.229252 0.000000
103 1.005952 1.005952 1.005952 1.005952 1.005952
104 1.005952 1.034325 1.087743 1.229252 1.355112
105 1.005952 1.034325 1.077577 1.077577 1.077577
106 1.005952 1.005952 1.005952 1.005952 1.005952
107 1.005952 1.034325 1.077577 1.077577 1.077577
108 1.005952 1.034325 1.087743 1.229252 1.402257
109 1.005952 1.034325 0.000000 0.000000 0.000000
110 1.005952 1.034325 1.087743 1.229252 1.402257
111 1.005952 1.034325 1.087743 1.229252 1.402257
112 1.005952 1.034325 1.087743 1.229252 1.355112
113 1.005952 1.034325 1.087743 1.229252 1.402257
114 1.005952 1.034325 1.087743 1.229252 1.402257
115 1.005952 1.034325 1.087743 1.229252 1.402257
116 1.005952 0.000000 0.000000 0.000000 0.000000
117 1.005952 1.034325 1.087743 1.229252 1.334264
118 1.005952 1.034325 1.087743 1.229252 1.402257
119 1.005952 1.034325 1.087743 1.229252 1.402257
120 1.005952 1.034325 1.087743 1.087743 1.087743
121 1.005952 0.000000 0.000000 0.000000 0.000000
122 1.005952 1.034325 1.087743 1.229252 1.402257
123 1.005952 1.034325 1.087743 1.229252 1.402257
124 1.005952 1.034325 1.087743 1.229252 1.229252
125 1.005952 1.034325 1.087743 1.229252 1.402257
126 1.005952 1.034325 1.087743 1.229252 1.402257
127 1.005952 1.034325 1.087743 1.229252 1.402257
128 1.005952 1.034325 1.087743 0.000000 0.000000
129 1.005952 1.034325 1.087743 1.229252 1.402257
130 1.005952 1.012570 1.012570 1.012570 1.012570
131 1.005952 1.034325 1.087743 1.171405 1.171405
132 1.005952 1.034325 1.087743 1.171405 1.171405
133 1.005952 1.034325 1.087743 1.229252 0.000000
134 1.005952 1.026489 1.026489 1.026489 1.026489
135 1.005952 1.034325 1.087743 1.229252 1.402257
136 1.005952 1.034325 1.087743 0.000000 0.000000
137 1.005952 1.034325 1.087743 1.229252 1.402257
138 1.005952 1.034325 1.087743 1.229252 1.334264
139 1.005952 1.034325 1.087743 1.229252 1.402257
140 1.005952 1.034325 1.087743 1.229252 0.000000
141 1.005952 1.034325 1.087743 1.229252 1.244812
142 1.005952 1.034325 1.087743 1.145515 1.145515
143 0.000000 0.000000 0.000000 0.000000 0.000000
144 1.000000 1.000000 1.000000 1.000000 1.000000
145 1.005952 1.034325 1.087743 0.000000 0.000000
146 1.005952 1.034325 1.087743 1.229252 1.402257
147 1.005952 1.034325 1.087743 1.229252 1.355112
148 1.005952 1.034325 1.087743 1.229252 1.402257
149 1.005952 1.034325 1.087743 1.229252 1.402257
150 1.005952 1.026489 1.026489 1.026489 1.026489
151 1.005952 1.034325 1.077577 1.077577 1.077577
152 1.005952 1.034325 1.087743 0.000000 0.000000
153 1.005952 1.034325 1.087743 1.158243 1.158243
154 1.005952 1.026489 1.026489 1.026489 1.026489
155 1.005952 1.034325 1.087743 0.000000 0.000000
156 1.005952 1.034325 1.087743 1.229252 1.402257
157 1.005952 1.034325 1.050551 1.050551 1.050551
158 1.005952 1.034325 1.087743 1.229252 1.402257
159 1.005952 1.026489 1.026489 1.026489 1.026489
160 1.005952 1.034325 1.087743 1.229252 0.000000
161 1.005952 1.034325 1.087743 1.229252 1.402257
162 1.005952 1.005952 1.005952 1.005952 1.005952
163 1.005952 1.034325 1.034325 1.034325 1.034325
164 1.005952 1.034325 1.087743 1.109718 1.109718
165 1.005952 1.034325 1.087743 0.000000 0.000000
166 1.005952 1.034325 1.087743 1.229252 1.402257
167 1.005952 1.034325 1.087743 1.229252 0.000000
168 1.005952 1.034325 1.087743 1.229252 1.296679
169 1.005952 1.026489 1.026489 1.026489 1.026489
170 1.005952 1.005952 1.005952 1.005952 1.005952
171 1.005952 1.034325 1.087743 1.229252 1.402257
172 1.005952 1.034325 1.087743 1.087743 1.087743
173 1.000000 1.000000 1.000000 1.000000 1.000000
174 1.005952 1.034325 1.087743 0.000000 0.000000
175 1.005952 1.034325 1.077577 1.077577 1.077577
>
> ## with covariates in the censoring model
> eC2.wglm <- wglm(Surv(time,event) ~ X1 + X8, formula.censor = ~ X1*X8,
+ times = tau, data = dSurv)
> eC2.wglm
IPCW logistic regression for cause 1
- structure: Surv(time, event) with possible states: 0, 1.
- censoring model: ~X1 * X8 (fitter: coxph function).
- outcome model: ~X1 + X8 (fitter: glm function).
- estimated regression parameters:
n.censor n.event IPCW(max) (Intercept) X11 X8
1 1 17 1.015908 -3.10140321 1.2426634 1.0768976
2 5 39 1.091976 -1.56792187 0.4646117 0.6977025
3 11 58 1.241579 -0.94962662 0.5895212 0.7033084
4 22 73 1.682909 -0.43630815 0.6413545 0.5335177
5 31 89 1.647757 0.06095976 1.6733406 0.4567761
>
> #### Competing risks ####
> ## here Kaplan-Meier as censoring model
> eCR.wglm <- wglm(Surv(time,event) ~ X1, formula.censor = ~X1,
+ times = tau, data = d)
Flavor: r-devel-windows-x86_64
Version: 2025.05.15
Check: installed package size
Result: NOTE
installed size is 12.0Mb
sub-directories of 1Mb or more:
R 2.1Mb
libs 9.4Mb
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64
Current CRAN status: NOTE: 6, OK: 7
Version: 2024.04.10
Check: Rd cross-references
Result: NOTE
Found the following Rd file(s) with Rd \link{} targets missing package
anchors:
plot.idm.Rd: SmartControl
Please provide package anchors for all Rd \link{} targets not in the
package itself and the base packages.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-windows-x86_64, r-patched-linux-x86_64, r-release-linux-x86_64, r-release-windows-x86_64