cif_est {cmprskcoxmsm}

Estimated cumulative incidence function

Description

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.

Usage

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

Arguments

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.

Details

After estimating the parameters in the cause-specific hazard \lambda_{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{\Lambda}_{j}^a(u),

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

Value

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.

References

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.