data.trim: Trim the data
In lilywang1988/IAfrac: Tools for weighted log-rank tests

Description Usage Arguments Details Value Author(s) See Also

Trim the data according to event number or time

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data.trim(t, data, trimmed = F)

data.trim.d(d, data, trimmed = F)

`t`	Time of interest to pause/stop the study, which could be an interim stage or the final stage.
`data`	There are two possible structures allowed for this input data. The first type needs to have `trimmed=F` and include variables: a `treatment` variable with "experimental" denoting treatment group, `cnsr` variable with value 1 denoting censoring, `ct` variable denoting event time from the origin of the study, which equals the sum of entering time `enterT` and the survival time (time to event or censoring). A dataset simulated from from R package nphsim should fit the first type well enough (see the example1). The second type can be any data.frame or data.table output from a `data.trim` function, including variables: `ct` denoting event time from the origin of the study or the sum of entering time and the survival time, `survival` denoting the survival time or time to event/censoring, `delta` as an event indicator, `enterT` as entering time (example 2). For the second type, we set `trimmed=T` to avoid extra computations, but should be fine if `trimmed=F`.
`trimmed`	Whether this data has been trimmed by `data.trim` or `data.trim.d` before.
`d`	Event counts to pause/stop the study.

data.trim is to trim the data upto t, data.trim.d is to trim the data upto the cound d.

Note that data.trim only outputs a data.table odered by ct, the event/censoring time since the start of the study (calendar scale), including variables in the input data.table/frame data, and additional/updated variables of event indicator delta, ct, follow-up time survival since the enrollment. data.trim.d outpus a list of two components. The first component is the data censored with d events have been observed, ordered by ct, the event/censoring time since the start of the study (calendar scale). The second component is the time of the stopping point when d events have been observed.