gen_stan_dat: Fit MAP estimates for the Poisson Model PEM. Important...
In csetraynor/iclust2prog: Prognostic modeling of IntClust-2 (iclust2prog)
Description
Usage
Arguments
Value
Description
Fit MAP estimates for the Poisson Model PEM. Important aspects of the modelling #'approach: Dependent variable is the binary event indicator. Adding an intercept is #'recommendable to provide a decent and interpretable reference category for factor #'variables. Use the logarithm of the interval length as an offset.
Usage
1
gen_stan_dat(dat, status = "status", time = "time", timepoints = T)
Arguments
d
a dataset
formula
a log baseline hazard
t_dur duration time for individtual ith in the hth interval
lambda hazard rate
os_event censoring indicator (actual event) for the ith subject in the hth interval
Value
a MAP fit
csetraynor/iclust2prog documentation built on May 7, 2019, 8:38 a.m.
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Description Usage Arguments Value
Description
Fit MAP estimates for the Poisson Model PEM. Important aspects of the modelling #'approach: Dependent variable is the binary event indicator. Adding an intercept is #'recommendable to provide a decent and interpretable reference category for factor #'variables. Use the logarithm of the interval length as an offset.
Usage
1 | gen_stan_dat(dat, status = "status", time = "time", timepoints = T)
|
Arguments
d |
a dataset |
Value
a MAP fit
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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