a b/README.md 

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<div class="sc-cmRAlD dkqmWS"><div class="sc-UEtKG dGqiYy sc-flttKd cguEtd"><div class="sc-fqwslf gsqkEc"><div class="sc-cBQMlg kAHhUk"><h2 class="sc-dcKlJK sc-cVttbi gqEuPW ksnHgj">About Dataset</h2></div></div></div><div class="sc-jgvlka jFuPjz"><div class="sc-gzqKSP tNtjD"><div style="min-height: 80px;"><div class="sc-etVRix jqYJaa sc-bMmLMY ZURWJ"><pre class="uc-code-block"><code><span class="hljs-built_in">Data</span> <span class="hljs-keyword">on</span> recurrences of bladder cancer, used <span class="hljs-keyword">by</span> many people <span class="hljs-keyword">to</span> demonstrate methodology for recurrent event modelling.





  
  

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</code><div class="uc-code-block-copy-button-wrapper"><button class="uc-code-block-copy-button google-symbols" aria-label="Copy code">content_copy</button></div></pre>





  
  

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<table>





  
  

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<thead>





  
  

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<tr>





  
  

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<th>Column</th>





  
  

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<th>Description</th>





  
  

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<th>Format</th>





  
  

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</tr>





  
  

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</thead>





  
  

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<tbody>





  
  

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<tr>





  
  

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<td><strong>Bladder Dataset 1</strong></td>





  
  

  14
  
<td></td>





  
  

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<td></td>





  
  

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</tr>





  
  

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<tr>





  
  

  18
  
<td>id</td>





  
  

  19
  
<td>Patient ID</td>





  
  

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<td></td>





  
  

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</tr>





  
  

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<tr>





  
  

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<td>treatment</td>





  
  

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<td>Treatment received</td>





  
  

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<td>Placebo, pyridoxine (vitamin B6), or thiotepa</td>





  
  

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</tr>





  
  

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<tr>





  
  

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<td>number</td>





  
  

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<td>Initial number of tumors</td>





  
  

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<td>8=8 or more</td>





  
  

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</tr>





  
  

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<tr>





  
  

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<td>size</td>





  
  

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<td>Size (cm) of largest initial tumor</td>





  
  

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<td></td>





  
  

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</tr>





  
  

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<tr>





  
  

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<td>recur</td>





  
  

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<td>Number of recurrences</td>





  
  

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<td></td>





  
  

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</tr>





  
  

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<tr>





  
  

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<td>start</td>





  
  

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<td>Start time of each interval</td>





  
  

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<td></td>





  
  

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</tr>





  
  

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<tr>





  
  

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<td>stop</td>





  
  

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<td>End time of each interval</td>





  
  

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<td></td>





  
  

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</tr>





  
  

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<tr>





  
  

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<td>status</td>





  
  

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<td>End of interval code</td>





  
  

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<td>0=censored, 1=recurrence, 2=death from bladder disease, 3=death other/unknown cause</td>





  
  

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</tr>





  
  

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<tr>





  
  

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<td>rtumor</td>





  
  

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<td>Number of tumors found at recurrence</td>





  
  

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<td></td>





  
  

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</tr>





  
  

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<tr>





  
  

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<td>rsize</td>





  
  

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<td>Size of largest tumor at recurrence</td>





  
  

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<td></td>





  
  

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</tr>





  
  

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<tr>





  
  

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<td>enum</td>





  
  

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<td>Event number (observation number within patient)</td>





  
  

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<td></td>





  
  

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</tr>





  
  

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<tr>





  
  

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<td><strong>Bladder Dataset 0</strong></td>





  
  

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<td></td>





  
  

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<td></td>





  
  

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</tr>





  
  

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<tr>





  
  

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<td>id</td>





  
  

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<td>Patient ID</td>





  
  

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<td></td>





  
  

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</tr>





  
  

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<tr>





  
  

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<td>rx</td>





  
  

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<td>Treatment received</td>





  
  

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<td>1=placebo, 2=thiotepa</td>





  
  

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</tr>





  
  

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<tr>





  
  

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<td>number</td>





  
  

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<td>Initial number of tumors</td>





  
  

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<td>8=8 or more</td>





  
  

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</tr>





  
  

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<tr>





  
  

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<td>size</td>





  
  

  94
  
<td>Size (cm) of largest initial tumor</td>





  
  

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<td></td>





  
  

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</tr>





  
  

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<tr>





  
  

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<td>stop</td>





  
  

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<td>Recurrence or censoring time</td>





  
  

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<td></td>





  
  

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</tr>





  
  

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<tr>





  
  

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<td>enum</td>





  
  

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<td>Which recurrence (up to 4)</td>





  
  

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<td></td>





  
  

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</tr>





  
  

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<tr>





  
  

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<td><strong>Bladder Dataset 2</strong></td>





  
  

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<td></td>





  
  

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<td></td>





  
  

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</tr>





  
  

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<tr>





  
  

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<td>id</td>





  
  

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<td>Patient ID</td>





  
  

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<td></td>





  
  

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</tr>





  
  

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<tr>





  
  

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<td>rx</td>





  
  

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<td>Treatment received</td>





  
  

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<td>1=placebo, 2=thiotepa</td>





  
  

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</tr>





  
  

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<tr>





  
  

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<td>number</td>





  
  

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<td>Initial number of tumors</td>





  
  

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<td>8=8 or more</td>





  
  

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</tr>





  
  

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<tr>





  
  

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<td>size</td>





  
  

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<td>Size (cm) of largest initial tumor</td>





  
  

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<td></td>





  
  

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</tr>





  
  

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<tr>





  
  

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<td>start</td>





  
  

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<td>Start of interval (0 or previous recurrence time)</td>





  
  

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<td></td>





  
  

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</tr>





  
  

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<tr>





  
  

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<td>stop</td>





  
  

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<td>Recurrence or censoring time</td>





  
  

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<td></td>





  
  

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</tr>





  
  

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<tr>





  
  

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<td>enum</td>





  
  

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<td>Which recurrence (up to 4)</td>





  
  

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<td></td>





  
  

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</tr>





  
  

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</tbody>





  
  

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</table>





  
  

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<pre class="uc-code-block"><code>Bladder is <span class="hljs-keyword">the</span> data <span class="hljs-built_in">set</span> that appears most commonly <span class="hljs-keyword">in</span> <span class="hljs-keyword">the</span> literature. It uses only <span class="hljs-keyword">the</span> <span class="hljs-number">85</span> subjects <span class="hljs-keyword">with</span> nonzero follow-up who were assigned <span class="hljs-built_in">to</span> either thiotepa <span class="hljs-keyword">or</span> placebo, <span class="hljs-keyword">and</span> only <span class="hljs-keyword">the</span> <span class="hljs-keyword">first</span> <span class="hljs-literal">four</span> recurrences <span class="hljs-keyword">for</span> <span class="hljs-keyword">any</span> patient. The status <span class="hljs-built_in">variable</span> is <span class="hljs-number">1</span> <span class="hljs-keyword">for</span> recurrence <span class="hljs-keyword">and</span> <span class="hljs-number">0</span> <span class="hljs-keyword">for</span> everything <span class="hljs-keyword">else</span> (including death <span class="hljs-keyword">for</span> <span class="hljs-keyword">any</span> reason). The data <span class="hljs-built_in">set</span> is laid out <span class="hljs-keyword">in</span> <span class="hljs-keyword">the</span> competing risks <span class="hljs-built_in">format</span> <span class="hljs-keyword">of</span> <span class="hljs-keyword">the</span> paper <span class="hljs-keyword">by</span> Wei, Lin, <span class="hljs-keyword">and</span> Weissfeld.





  
  

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<pre class="uc-code-block"><code>Bladder1 is <span class="hljs-keyword">the</span> full data <span class="hljs-built_in">set</span> <span class="hljs-built_in">from</span> <span class="hljs-keyword">the</span> study. It <span class="hljs-keyword">contains</span> all <span class="hljs-literal">three</span> treatment arms <span class="hljs-keyword">and</span> all recurrences <span class="hljs-keyword">for</span> <span class="hljs-number">118</span> subjects; <span class="hljs-keyword">the</span> maximum observed <span class="hljs-built_in">number</span> <span class="hljs-keyword">of</span> recurrences is <span class="hljs-number">9.</span>





  
  

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</code><div class="uc-code-block-copy-button-wrapper"><button class="uc-code-block-copy-button google-symbols" aria-label="Copy code">content_copy</button></div></pre>





  
  

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<pre class="uc-code-block"><code>Bladder2 uses <span class="hljs-keyword">the</span> same subset <span class="hljs-keyword">of</span> subjects <span class="hljs-keyword">as</span> bladder, but formatted <span class="hljs-keyword">in</span> <span class="hljs-keyword">the</span> (<span class="hljs-built_in">start</span>, <span class="hljs-built_in">stop</span>] <span class="hljs-keyword">or</span> Anderson-Gill style. Note that <span class="hljs-keyword">in</span> transforming <span class="hljs-built_in">from</span> <span class="hljs-keyword">the</span> WLW <span class="hljs-built_in">to</span> <span class="hljs-keyword">the</span> AG style data <span class="hljs-built_in">set</span> there is <span class="hljs-keyword">a</span> quite common programming mistake that leads <span class="hljs-built_in">to</span> extra follow-up <span class="hljs-built_in">time</span> <span class="hljs-keyword">for</span> <span class="hljs-number">12</span> subjects: all those <span class="hljs-keyword">with</span> follow-up beyond their <span class="hljs-number">4</span>th recurrence. This <span class="hljs-string">"follow-up"</span> is <span class="hljs-keyword">a</span> side effect <span class="hljs-keyword">of</span> throwing away all events <span class="hljs-keyword">after</span> <span class="hljs-keyword">the</span> <span class="hljs-keyword">fourth</span> <span class="hljs-keyword">while</span> retaining <span class="hljs-keyword">the</span> <span class="hljs-keyword">last</span> follow-up <span class="hljs-built_in">time</span> <span class="hljs-built_in">variable</span> <span class="hljs-built_in">from</span> <span class="hljs-keyword">the</span> original data. The bladder2 data <span class="hljs-built_in">set</span> found here does <span class="hljs-keyword">not</span> make this mistake, but some analyses <span class="hljs-keyword">in</span> <span class="hljs-keyword">the</span> literature have done so; <span class="hljs-keyword">it</span> results <span class="hljs-keyword">in</span> <span class="hljs-keyword">the</span> addition <span class="hljs-keyword">of</span> <span class="hljs-keyword">a</span> small amount <span class="hljs-keyword">of</span> immortal <span class="hljs-built_in">time</span> bias <span class="hljs-keyword">and</span> shrinks <span class="hljs-keyword">the</span> fitted coefficients towards <span class="hljs-literal">zero</span>.





  
  

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