This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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135
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Type:
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Contributed
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Date/Time:
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Monday, August 2, 2010 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistical Computing
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Abstract - #308204 |
Title:
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Software for Targeted Maximum Likelihood Estimation
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Author(s):
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Susan Gruber*+ and Mark J. Van der Laan
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Companies:
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University of California, Berkeley and University of California, Berkeley
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Address:
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6415 Myrtlewood Drive, Cupertino, CA, 95014,
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Keywords:
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software ;
targeted maximum likelihood estimation ;
application ;
R ;
biostatistics
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Abstract:
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Traditional parametric modeling approaches to effect estimation cannot be successfully applied to many data-driven health-related questions of interest to researchers today, and great strides have been made in developing alternate approaches. Targeted maximum likelihood estimation (TMLE), a double robust semiparametric approach to causal and non-causal (variable importance) effect estimation, is being applied in diverse application areas including survival analysis, safety analysis, comparative effectiveness research, and genomics. This talk introduces two publicly available R packages that implement TMLE for additive point treatment effect estimation: "tmleLite," a basic TMLE implementation, and "ctmleLite", for collaborative targeted maximum likelihood estimation (C-TMLE). Essential aspects of TMLE methodology will be highlighted as each package is demonstrated.
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