rtpwexp

Obtains random samples from a truncated piecewise
exponential distribution.

Performs power and sample size calculation for non-proportional hazards model using the Fleming-Harrington family of weighted log-rank tests. The sequentially calculated log-rank test score statistics are assumed to have independent increments as characterized in Anastasios A. Tsiatis (1982) <doi:10.1080/01621459.1982.10477898>. The mean and variance of log-rank test score statistics are calculated based on Kaifeng Lu (2021) <doi:10.1002/pst.2069>. The boundary crossing probabilities are calculated using the recursive integration algorithm described in Christopher Jennison and Bruce W. Turnbull (2000, ISBN:0849303168). The package can also be used for continuous, binary, and count data. For continuous data, it can handle missing data through mixed-model for repeated measures (MMRM). In crossover designs, it can estimate direct treatment effects while accounting for carryover effects. For binary data, it can design Simon's 2-stage, modified toxicity probability-2 (mTPI-2), and Bayesian optimal interval (BOIN) trials. For count data, it can design group sequential trials for negative binomial endpoints with censoring. Additionally, it facilitates group sequential equivalence trials for all supported data types. Moreover, it can design adaptive group sequential trials for changes in sample size, error spending function, number and spacing or future looks. Finally, it offers various options for adjusted p-values, including graphical and gatekeeping procedures.

Kaifeng Lu

lrstat

Power and Sample Size Calculation for Non-Proportional Hazards
and Beyond

rtpwexp function

<dl><dt>n</dt>
<dd>The number of observations.</dd>
<dt>piecewiseSurvivalTime</dt>
<dd>A vector that specifies the starting time of
piecewise exponential survival time intervals. Must start with 0, e.g.,
<code>c(0, 6)</code> breaks the time axis into 2 event intervals:
[0, 6) and [6, Inf).
Defaults to 0 for exponential distribution.</dd>
<dt>lambda</dt>
<dd>A vector of hazard rates for the event. One for
each analysis time interval.</dd>
<dt>lowerBound</dt>
<dd>The left truncation time point for the survival time.
Defaults to 0 for no truncation.</dd></dl>

Arguments

Kaifeng Lu, <a href="/link/kaifenglu%40gmail.com?package=lrstat&version=0.2.13" data-mini-rdoc="lrstat::kaifenglu@gmail.com">kaifenglu@gmail.com</a>

Author

Random Number Generation Function of Truncated Piecewise
Exponential Distribution — rtpwexp

<dl>

<dt>n</dt>
<dd>The number of observations.</dd>


<dt>piecewiseSurvivalTime</dt>
<dd>A vector that specifies the starting time of
piecewise exponential survival time intervals. Must start with 0, e.g.,
<code>c(0, 6)</code> breaks the time axis into 2 event intervals:
[0, 6) and [6, Inf).
Defaults to 0 for exponential distribution.</dd>


<dt>lambda</dt>
<dd>A vector of hazard rates for the event. One for
each analysis time interval.</dd>


<dt>lowerBound</dt>
<dd>The left truncation time point for the survival time.
Defaults to 0 for no truncation.</dd>

</dl>

Kaifeng Lu, <a href='mailto:kaifenglu@gmail.com'>kaifenglu@gmail.com</a>

rtpwexp: Random Number Generation Function of Truncated Piecewise Exponential Distribution

Description

Usage

Value

Arguments

Author

Examples