cif_est: Estimated cumulative incidence function
In cmprskcoxmsm: Use IPW to Estimate Treatment Effect under Competing Risks

Description Usage Arguments Details Value References

View source: R/cif_est.R

cif_est estimates the cumulative incidence function (CIF, i.e.risk) based on the cause-specific regression results with 95% confidence intervals, it also calculates the risk ratio and risk difference for the specific time point.

cif_est(data=,
        time, time2 = NULL,
        Event.var, Events, cif.event,
        weight.type,
        ties = NULL,
        risktab = TRUE, risk.time = NULL)

`data`	The dataset, output of `doPS`
`time`	See `weight_cause_cox`.
`time2`	See `weight_cause_cox`.
`Event.var`	The variable name for the event indicator which typically has at least 3 levels.
`Events`	The vector of all the event name, the rest of levels in the `Event.var` will be treated as loss to follow up (i.e. right censoring).
`cif.event`	Value of event of interest for the CIF.
`weight.type`	See `weight_cause_cox`.
`ties`	See `weight_cause_cox`.
`risktab`	Indicator whether the risk ratio and risk difference table should be returned.
`risk.time`	If `risktab`, the specific time point for calculating the risk ratio and risk difference.

After estimating the parameters in the cause-specific hazard λ_{j}^a using IPW, we could estimate the corresponding CIF:

\hat{P}(T^a<t,J^a=j) = \int_{0}^{t} \hat{S}^a(u) d\hat{Λ}_{j}^a(u),

where \hat{S}^a is the estimated overall survial function for T^a, \hat{S}^a(u) = e^{-∑_j\hat{Λ}_{j}^a(u)}, \hatΛ_{j}^a(u) = \hatΛ_{0j}(u)e^{\hatβ*a}, and \hatΛ_{0j}(u) is a Breslow-type estimator of the baseline cumulative hazard.

Returns a table containing the estimated CIF for the event of interest for control and treated group and their 95% confidence intervals.

If risktab, will return the risk ratio and risk difference at time risk.time, and their 95% confidence intervals.

Hou, J., Paravati, A., Hou, J., Xu, R., & Murphy, J. (2018). “High-dimensional variable selection and prediction under competing risks with application to SEER-Medicare linked data,” Statistics in Medicine 37(24), 3486-3502.

cmprskcoxmsm documentation built on Sept. 5, 2021, 5:10 p.m.