Title |
Graphical modeling of binary data using the LASSO: a simulation study
|
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Published in |
BMC Medical Research Methodology, February 2012
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DOI | 10.1186/1471-2288-12-16 |
Pubmed ID | |
Authors |
Ralf Strobl, Eva Grill, Ulrich Mansmann |
Abstract |
Graphical models were identified as a promising new approach to modeling high-dimensional clinical data. They provided a probabilistic tool to display, analyze and visualize the net-like dependence structures by drawing a graph describing the conditional dependencies between the variables. Until now, the main focus of research was on building Gaussian graphical models for continuous multivariate data following a multivariate normal distribution. Satisfactory solutions for binary data were missing. We adapted the method of Meinshausen and Bühlmann to binary data and used the LASSO for logistic regression. Objective of this paper was to examine the performance of the Bolasso to the development of graphical models for high dimensional binary data. We hypothesized that the performance of Bolasso is superior to competing LASSO methods to identify graphical models. |
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