Last updated on 2025-12-06 00:48:46 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.2.1.1 | 9.80 | 83.71 | 93.51 | OK | |
| r-devel-linux-x86_64-debian-gcc | 1.2.1.1 | 6.68 | 47.31 | 53.99 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 1.2.1.1 | 21.00 | 118.54 | 139.54 | OK | |
| r-devel-linux-x86_64-fedora-gcc | 1.2.1.1 | 22.00 | 111.77 | 133.77 | OK | |
| r-devel-windows-x86_64 | 1.2.1.1 | 10.00 | 92.00 | 102.00 | OK | |
| r-patched-linux-x86_64 | 1.2.1.1 | 10.15 | 77.36 | 87.51 | OK | |
| r-release-linux-x86_64 | 1.2.1.1 | 9.12 | 78.95 | 88.07 | OK | |
| r-release-macos-arm64 | 1.2.1.1 | OK | ||||
| r-release-macos-x86_64 | 1.2.1.1 | 9.00 | 73.00 | 82.00 | OK | |
| r-release-windows-x86_64 | 1.2.1.1 | 10.00 | 97.00 | 107.00 | OK | |
| r-oldrel-macos-arm64 | 1.2.1.1 | OK | ||||
| r-oldrel-macos-x86_64 | 1.2.1.1 | 8.00 | 76.00 | 84.00 | OK | |
| r-oldrel-windows-x86_64 | 1.2.1.1 | 14.00 | 112.00 | 126.00 | OK |
Version: 1.2.1.1
Check: examples
Result: ERROR
Running examples in ‘ipw-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: ipwpoint
> ### Title: Estimate Inverse Probability Weights (Point Treatment)
> ### Aliases: ipwpoint
> ### Keywords: htest models
>
> ### ** Examples
>
> #Simulate data with continuous confounder and outcome, binomial exposure.
> #Marginal causal effect of exposure on outcome: 10.
> n <- 1000
> simdat <- data.frame(l = rnorm(n, 10, 5))
> a.lin <- simdat$l - 10
> pa <- exp(a.lin)/(1 + exp(a.lin))
> simdat$a <- rbinom(n, 1, prob = pa)
> simdat$y <- 10*simdat$a + 0.5*simdat$l + rnorm(n, -10, 5)
> simdat[1:5,]
l a y
1 6.867731 0 -2.315917
2 10.918217 0 -9.167457
3 5.821857 0 -2.621165
4 17.976404 1 4.283153
5 11.647539 1 8.518530
>
> #Estimate ipw weights.
> temp <- ipwpoint(
+ exposure = a,
+ family = "binomial",
+ link = "logit",
+ numerator = ~ 1,
+ denominator = ~ l,
+ data = simdat)
> summary(temp$ipw.weights)
Min. 1st Qu. Median Mean 3rd Qu. Max.
0.4950 0.5050 0.5163 0.8905 0.6100 89.0982
>
> #Plot inverse probability weights
> graphics.off()
> ipwplot(weights = temp$ipw.weights, logscale = FALSE,
+ main = "Stabilized weights", xlim = c(0, 8))
>
> #Examine numerator and denominator models.
> summary(temp$num.mod)
Call:
glm(formula = a ~ 1, family = "logit", data = simdat, na.action = na.fail)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 0.02000 0.06325 0.316 0.752
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 1386.2 on 999 degrees of freedom
Residual deviance: 1386.2 on 999 degrees of freedom
AIC: 1388.2
Number of Fisher Scoring iterations: 3
> summary(temp$den.mod)
Call:
glm(formula = a ~ l, family = "logit", data = simdat, na.action = na.fail)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -10.08091 0.71644 -14.07 <2e-16 ***
l 1.02239 0.07202 14.20 <2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 1386.19 on 999 degrees of freedom
Residual deviance: 464.46 on 998 degrees of freedom
AIC: 468.46
Number of Fisher Scoring iterations: 7
>
> #Paste inverse probability weights
> simdat$sw <- temp$ipw.weights
>
> #Marginal structural model for the causal effect of a on y
> #corrected for confounding by l using inverse probability weighting
> #with robust standard error from the survey package.
> require("survey")
Loading required package: survey
Warning in library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, :
there is no package called ‘survey’
> msm <- (svyglm(y ~ a, design = svydesign(~ 1, weights = ~ sw,
+ data = simdat)))
Error in svyglm(y ~ a, design = svydesign(~1, weights = ~sw, data = simdat)) :
could not find function "svyglm"
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc