High-Performance Open-Source Archive
The user interface for robin_surv has been improved
for specifying analysis stratification variables directly as part of the
model formula, similar to how it is done in
survival::coxph. In addition, the randomization scheme is
now specified as for the other RobinCar2 functions for
consistency. A warning will be issued when the randomization strata are
not adequately included in the analysis model. See the updated vignette
for details.
It is now possible to only perform the log rank test, without
estimating the log hazard ratio, in robin_surv by setting
the argument contrast = "none". This can be useful
e.g. when performing simulation studies focusing only on the log-rank
test operating characteristics, because the log-rank test is
computationally less expensive than estimating the hazard
ratio.
Fixed a bug in covariate-adjusted stratified survival function
estimation in robin_surv which could occur when there are
character covariates with values only appearing in one stratum, which
could have failed or lead to incorrect results.
Fixed a issue in robin_lm that variance method does
not apply correctly.
Fixed a issue in robin_glm that vcovHC
could previously be used for non-Gaussian family.
Fixed another bug in covariate-adjusted stratified survival
function estimation in robin_surv, which resulted from
design matrices separately derived per stratum. Now the design matrix is
created once including the stratum indicator, and then the
stratum-specific parts are extracted as needed.
sp to sr which is easier to
read as “simple randomization”.robin_surv objects has been
improved for better readability.robin_surv by adding them on the right-hand side of the
treatment formula.robin_surv
during the hazard ratio estimation coming from the variance calculation:
Now the variance is only calculated after the hazard ratio estimate is
obtained.robin_surv, the function now works correctly and does not
fail with a “singular design matrix” error any longer.robin_surv which could occur when there are character
covariates with values only appearing in one treatment group, which
could have led to incorrect results.log_odds_ratio and log_risk_ratio
function for inference.contrast_mat to treatment_effect
object.confint to obtain confidence interval for
prediction_cf and treatment_effect
object.robin_glm, vcovG is always
used regardless the variance type argument. This is fixed now.robin_glm and
robin_lm.
Need mirroring services?
Contact our team at info@vpspulse.com.
Mirror powered by VPSpulse
Infrastructure sponsored by VPSPulse & Secure Payments by ArionPay.