kmest

Obtains the Kaplan-Meier estimates of the survival curve.

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

kmest function

<dl><dt>data</dt>
<dd>The input data frame that contains the following variables:<ul>
<li><code>rep</code>: The replication for by-group processing.</li>
<li><code>stratum</code>: The stratum.</li>
<li><code>time</code>: The possibly right-censored survival time.</li>
<li><code>event</code>: The event indicator.</li>
</ul></dd>
<dt>rep</dt>
<dd>The name(s) of the replication variable(s) in the input data.</dd>
<dt>stratum</dt>
<dd>The name(s) of the stratum variable(s) in the input data.</dd>
<dt>time</dt>
<dd>The name of the time variable in the input data.</dd>
<dt>event</dt>
<dd>The name of the event variable in the input data.</dd>
<dt>conftype</dt>
<dd>The type of the confidence interval. One of "none",
"plain", "log", "log-log" (the default), or "arcsin".
The arcsin option bases the intervals on asin(sqrt(survival)).</dd>
<dt>conflev</dt>
<dd>The level of the two-sided confidence interval for
the survival probabilities. Defaults to 0.95.</dd>
<dt>keep_censor</dt>
<dd>Whether to retain the censoring time in the output
data frame.</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

Kaplan-Meier Estimates of Survival Curve — kmest

<dl>

<dt>data</dt>
<dd>The input data frame that contains the following variables:<ul>
<li><code>rep</code>: The replication for by-group processing.</li>
<li><code>stratum</code>: The stratum.</li>
<li><code>time</code>: The possibly right-censored survival time.</li>
<li><code>event</code>: The event indicator.</li>
</ul></dd>


<dt>rep</dt>
<dd>The name(s) of the replication variable(s) in the input data.</dd>


<dt>stratum</dt>
<dd>The name(s) of the stratum variable(s) in the input data.</dd>


<dt>time</dt>
<dd>The name of the time variable in the input data.</dd>


<dt>event</dt>
<dd>The name of the event variable in the input data.</dd>


<dt>conftype</dt>
<dd>The type of the confidence interval. One of "none",
"plain", "log", "log-log" (the default), or "arcsin".
The arcsin option bases the intervals on asin(sqrt(survival)).</dd>


<dt>conflev</dt>
<dd>The level of the two-sided confidence interval for
the survival probabilities. Defaults to 0.95.</dd>


<dt>keep_censor</dt>
<dd>Whether to retain the censoring time in the output
data frame.</dd>

</dl>

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

kmest: Kaplan-Meier Estimates of Survival Curve

Description

Usage

Value

Arguments

Author

Examples