tag:crantastic.org,2005:/packages/multiPIMLatest activity for multiPIM2015-02-25T07:31:18Zcrantastic.orgtag:crantastic.org,2005:TimelineEvent/392322015-02-25T07:31:18Z2015-02-25T07:31:18ZmultiPIM was upgraded to version 1.4-3<a href="/packages/multiPIM">multiPIM</a> was <span class="action">upgraded</span> to version <a href="/packages/multiPIM/versions/39057">1.4-3</a><br /><h3>Package description:</h3><p>Performs variable importance analysis using a causal inference approach. This is done by fitting Population Intervention Models. The default is to use a Targeted Maximum Likelihood Estimator (TMLE). The other available estimators are Inverse Probability of Censoring Weighted (IPCW), Double-Robust IPCW (DR-IPCW), and Graphical Computation (G-COMP) estimators. Inference can be obtained from the influence curve (plug-in) or by bootstrapping.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/285902013-01-18T05:50:49Z2013-01-18T05:50:49ZmultiPIM was upgraded to version 1.3-1<a href="/packages/multiPIM">multiPIM</a> was <span class="action">upgraded</span> to version <a href="/packages/multiPIM/versions/24381">1.3-1</a><br /><h3>Package description:</h3><p>Performs variable importance analysis using a causal inference approach. This is done by fitting Population Intervention Models. The default is to use a Targeted Maximum Likelihood Estimator (TMLE). The other available estimators are Inverse Probability of Censoring Weighted (IPCW), Double-Robust IPCW (DR-IPCW), and Graphical Computation (G-COMP) estimators. Inference can be obtained from the influence curve (plug-in) or by bootstrapping.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/171232011-11-02T17:30:54Z2011-11-02T17:30:54ZmultiPIM was upgraded to version 1.2-1<a href="/packages/multiPIM">multiPIM</a> was <span class="action">upgraded</span> to version <a href="/packages/multiPIM/versions/15267">1.2-1</a><br /><h3>Package description:</h3><p>Performs variable importance analysis for possibly many exposures of interest and possibly many outcomes of interest. This is done by fitting Population Intervention Models. The default is to use a Targeted Maximum Likelihood Estimator (TMLE). The other available estimators are Inverse Probability of Censoring Weighted (IPCW), Double-Robust IPCW (DR-IPCW), and Graphical Computation (G-COMP) estimators. Inference can be obtained from the influence curve (plug-in) or by bootstrapping.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/162272011-09-20T19:30:21Z2011-09-20T19:30:21ZmultiPIM was upgraded to version 1.1-2<a href="/packages/multiPIM">multiPIM</a> was <span class="action">upgraded</span> to version <a href="/packages/multiPIM/versions/14442">1.1-2</a><br /><h3>Package description:</h3><p>Performs variable importance analysis for possibly many exposures of interest and possibly many outcomes of interest. This is done by fitting Population Intervention Models. The default is to use a Targeted Maximum Likelihood Estimator (TMLE). The other available estimators are Inverse Probability of Censoring Weighted (IPCW), Double-Robust IPCW (DR-IPCW), and Graphical Computation (G-COMP) estimators. Inference can be obtained from the influence curve (plug-in) or by bootstrapping.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/161052011-09-14T19:50:23Z2011-09-14T19:50:23ZmultiPIM was upgraded to version 1.1-1<a href="/packages/multiPIM">multiPIM</a> was <span class="action">upgraded</span> to version <a href="/packages/multiPIM/versions/14346">1.1-1</a><br /><h3>Package description:</h3><p>Performs variable importance analysis for possibly many exposures of interest and possibly many outcomes of interest. This is done by fitting Population Intervention Models. The default is to use a Targeted Maximum Likelihood Estimator (TMLE). The other available estimators are Inverse Probability of Censoring Weighted (IPCW), Double-Robust IPCW (DR-IPCW), and Graphical Computation (G-COMP) estimators. Inference can be obtained from the influence curve (plug-in) or by bootstrapping.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/133992011-05-05T09:10:26Z2011-05-05T09:10:26ZmultiPIM was released<a href="/packages/multiPIM">multiPIM</a> was <span class="action">released</span><br /><h3>Package description:</h3><p>Performs variable importance analysis using a causal inference approach. This is done by fitting Population Intervention Models. The default is to use a Targeted Maximum Likelihood Estimator (TMLE). The other available estimators are Inverse Probability of Censoring Weighted (IPCW), Double-Robust IPCW (DR-IPCW), and Graphical Computation (G-COMP) estimators. Inference can be obtained from the influence curve (plug-in) or by bootstrapping.</p>crantastic.org