bucher {maicplus} | R Documentation |
Bucher method for combining treatment effects
Description
Given two treatment effects of A vs. C and B vs. C derive the treatment effects of A vs. B using the Bucher method. Two-sided confidence interval and Z-test p-value are also calculated. Treatment effects and standard errors should be in log scale for hazard ratio, odds ratio, and risk ratio. Treatment effects and standard errors should be in natural scale for risk difference and mean difference.
Usage
bucher(trt, com, conf_lv = 0.95)
## S3 method for class 'maicplus_bucher'
print(x, ci_digits = 2, pval_digits = 3, exponentiate = FALSE, ...)
Arguments
trt |
a list of two scalars for the study with the
experimental arm. |
com |
same as |
conf_lv |
a numerical scalar, prescribe confidence level to derive two-sided confidence interval for the treatment effect |
x |
|
ci_digits |
an integer, number of decimal places for point estimate and derived confidence limits |
pval_digits |
an integer, number of decimal places to display Z-test p-value |
exponentiate |
whether the treatment effect and confidence interval should be exponentiated. This applies to relative treatment effects. Default is set to false. |
... |
not used |
Value
a list with 5 elements,
- est
a scalar, point estimate of the treatment effect
- se
a scalar, standard error of the treatment effect
- ci_l
a scalar, lower confidence limit of a two-sided CI with prescribed nominal level by
conf_lv
- ci_u
a scalar, upper confidence limit of a two-sided CI with prescribed nominal level by
conf_lv
- pval
p-value of Z-test, with null hypothesis that
est
is zero
Methods (by generic)
-
print(maicplus_bucher)
: Print method formaicplus_bucher
objects
Examples
trt <- list(est = log(1.1), se = 0.2)
com <- list(est = log(1.3), se = 0.18)
result <- bucher(trt, com, conf_lv = 0.9)
print(result, ci_digits = 3, pval_digits = 3)