Beibei Jiang <beibei_jiang@psych.mpg.de> and Benno Pütz <puetz@psych.mpg.de>
Searching genomic interactions with linear/logistic regression in a high-dimensional dataset is a time-consuming task. This package provides some efficient ways to scan epistasis in genome-wide interaction studies (GWIS). Both case-control status (binary outcome) and quantitative phenotype (continuous outcome) are supported (the main references: 1. Kam-Thong, T., D. Czamara, K. Tsuda, K. Borgwardt, C. M. Lewis, A. Erhardt-Lehmann, B. Hemmer, et al. (2011). <doi:10.1038/ejhg.2010.196>. 2. Kam-Thong, T., B. Pütz, N. Karbalai, B. Müller-Myhsok, and K. Borgwardt. (2011).  <doi:10.1093/bioinformatics/btr218>.)

Basic Sensitivity Analysis of Epidemiological Results
person("Denis", "Haine", email = "denis.haine@gmail.com",
role = c("aut", "cre"))
Basic sensitivity analysis of the observed relative risks adjusting
for unmeasured confounding and misclassification of the
exposure/outcome, or both. It follows the bias analysis methods and
examples from the book by Lash T.L, Fox M.P, and Fink A.K. Applying
Quantitative Bias Analysis to Epidemiologic Data, Springer, 2009.

triangle, trapezoid, plyr, ggplot2, grid, gridExtra
Basic sensitivity analysis of the observed relative risks adjusting
for unmeasured confounding and misclassification of the
exposure/outcome, or both. It follows the bias analysis methods and
examples from the book by Lash T.L, Fox M.P, and Fink A.K.
"Applying Quantitative Bias Analysis to Epidemiologic Data",
'Springer', 2009.

Basic sensitivity analysis of the observed relative risks adjusting
for unmeasured confounding and misclassification of the
exposure/outcome, or both. It follows the bias analysis methods and
examples from the book by Lash T.L, Fox M.P, and Fink A.K.
"Applying Quantitative Bias Analysis to Epidemiologic Data",
('Springer', 2009).

triangle, trapezoid, plyr, ggplot2, grid, gridExtra, reshape,
boot

triangle, trapezoid, actuar, llogistic, logitnorm, plyr,
ggplot2, grid, gridExtra, reshape, boot