dataCSL

<p>Survival status for the liver chirrosis patients of Schlichting et al.</p>

dataset

Numerous functions for cohort-based analyses, either for prediction or causal inference. For causal inference, it includes Inverse Probability Weighting and G-computation for marginal estimation of an exposure effect when confounders are expected. We deal with binary outcomes, times-to-events, competing events, and multi-state data. For multistate data, semi-Markov model with interval censoring may be considered, and we propose the possibility to consider the excess of mortality related to the disease compared to reference lifetime tables. For predictive studies, we propose a set of functions to estimate time-dependent receiver operating characteristic (ROC) curves with the possible consideration of right-censoring times-to-events or the presence of confounders. Finally, several functions are available to assess time-dependent ROC curves or survival curves from aggregated data.

Yohann Foucher

RISCA

Causal Inference and Prediction in Cohort-Based Analyses

dataCSL function

<p>This data frame contains the following columns:</p><table class="table">
<tr><td><code>id</code></td><td>a numeric vector related to the subject ID.</td></tr>
<tr><td><code>time</code></td><td>A numeric vector with the time of measurement.</td></tr>
<tr><td><code>prot</code></td><td>A numeric vector with the prothrombin level at measurement time.</td></tr>
<tr><td><code>dc</code></td><td>A numeric vector code. 0: censored observation, 1: died at eventT.</td></tr>
<tr><td><code>eventT</code></td><td>A numeric vector with the time of event (death).</td></tr>
<tr><td><code>treat</code></td><td>A numeric vector code. 0: active treatment of prednisone, 1: placebo treatment.</td></tr>
<tr><td><code>sex</code></td><td>A numeric vector code. 0: female, 1: male.</td></tr>
<tr><td><code>age</code></td><td>A numeric vector with the age of subject at inclusion time subtracted 60.</td></tr>
<tr><td><code>prot.base</code></td><td>A numeric vector with the prothrombin base level before entering the study</td></tr>
<tr><td><code>prot.prev</code></td><td>A numeric vector with the level of prothrombin at previous measurement time.</td></tr>
<tr><td><code>lt</code></td><td>A numeric vector with the starting time for the time-interval.</td></tr>
<tr><td><code>rt</code></td><td>A numeric vector with the stopping time for the time-interval.</td></tr>
</table><p></p><p></p>

Format

CSL Liver Chirrosis Data. — dataCSL

<p>This data frame contains the following columns:</p><table class='table'>
<tr><td><code>id</code></td><td>a numeric vector related to the subject ID.</td></tr>
<tr><td><code>time</code></td><td>A numeric vector with the time of measurement.</td></tr>
<tr><td><code>prot</code></td><td>A numeric vector with the prothrombin level at measurement time.</td></tr>
<tr><td><code>dc</code></td><td>A numeric vector code. 0: censored observation, 1: died at eventT.</td></tr>
<tr><td><code>eventT</code></td><td>A numeric vector with the time of event (death).</td></tr>
<tr><td><code>treat</code></td><td>A numeric vector code. 0: active treatment of prednisone, 1: placebo treatment.</td></tr>
<tr><td><code>sex</code></td><td>A numeric vector code. 0: female, 1: male.</td></tr>
<tr><td><code>age</code></td><td>A numeric vector with the age of subject at inclusion time subtracted 60.</td></tr>
<tr><td><code>prot.base</code></td><td>A numeric vector with the prothrombin base level before entering the study</td></tr>
<tr><td><code>prot.prev</code></td><td>A numeric vector with the level of prothrombin at previous measurement time.</td></tr>
<tr><td><code>lt</code></td><td>A numeric vector with the starting time for the time-interval.</td></tr>
<tr><td><code>rt</code></td><td>A numeric vector with the stopping time for the time-interval.</td></tr>
</table>



dataCSL: CSL Liver Chirrosis Data.

Description

Usage

Arguments

Format

References

Examples

`id`	a numeric vector related to the subject ID.
`time`	A numeric vector with the time of measurement.
`prot`	A numeric vector with the prothrombin level at measurement time.
`dc`	A numeric vector code. 0: censored observation, 1: died at eventT.
`eventT`	A numeric vector with the time of event (death).
`treat`	A numeric vector code. 0: active treatment of prednisone, 1: placebo treatment.
`sex`	A numeric vector code. 0: female, 1: male.
`age`	A numeric vector with the age of subject at inclusion time subtracted 60.
`prot.base`	A numeric vector with the prothrombin base level before entering the study
`prot.prev`	A numeric vector with the level of prothrombin at previous measurement time.
`lt`	A numeric vector with the starting time for the time-interval.
`rt`	A numeric vector with the stopping time for the time-interval.