# NOT RUN {
outputs <- list(
est = list(
th = list(CL = 0.482334, VC = 0.0592686),
om = list(nCL = 0.315414, nVC = 0.536025),
sg = list(ERRP = 0.0508497)),
se = list(
th = list(CL = 0.0138646, VC = 0.00555121),
om = list(nCL = 0.0188891, nVC = 0.0900352),
sg = list(ERRP = 0.00182851)),
fixed = list(
th = list(CL = FALSE, VC = FALSE),
om = list(nCL = FALSE, nVC = FALSE),
sg = list(ERRP = FALSE)),
shrinkage = list(nCL = 9.54556, nVC = 47.8771))
meta <- list(
parameters = list(
list(name="CL", label="Clearance", units="L/h", type="Structural"),
list(name="VC", label="Volume", units="L", type="Structural", trans="exp"),
list(name="nCL", label="On Clearance", type="IIV", trans="SD (CV%)"),
list(name="nVC", label="On Volume", type="IIV"),
list(name="ERRP", label="Proportional Error", units="%", type="RUV", trans="%")))
pmxpartab(pmxparframe(outputs, meta),
columns=c(est="Estimate", rse="RSE%", ci95="95% CI", shrinkage="Shrinkage"),
footnote="CI=confidence interval; RSE=relative standard error.")
# An example using a Cox model, where we construct the parframe manually:
library(survival)
cph.fit <- coxph(Surv(time, status) ~ ph.ecog + age, data=lung)
parframe <- with(summary(cph.fit), data.frame(
name = c("ph.ecog", "age"),
label = c("ECOG performance score", "Age"),
est = coefficients[,"exp(coef)"],
pval = coefficients[,"Pr(>|z|)"],
lci95 = conf.int[,"lower .95"],
uci95 = conf.int[,"upper .95"]
))
pmxpartab(parframe=parframe,
columns=c(est="HR", ci95="95% CI", pval="P-Value"))
# }
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