MapGAM: Mapping Smoothed Effect Estimates from Individual-Level Data

Contains functions for mapping odds ratios or other effect estimates using individual-level data such as case-control study data, using generalized additive models (GAMs) for smoothing with a two-dimensional predictor (e.g., geolocation or exposure to chemical mixtures) while adjusting for confounding variables, using methods described by Kelsall and Diggle (1998) and Webster at al. (2006). Includes convenient functions for mapping, efficient control sampling, and permutation tests for the null hypothesis that the two-dimensional predictor is not associated with the outcome variable (adjusting for confounders).

Version: 0.7-0
Depends: R (≥ 2.10.0), gam, maptools
Suggests: maps, mapproj, PBSmapping
Published: 2013-12-13
Author: Veronica Vieira, Scott Bartell, and Robin Bliss
Maintainer: Scott Bartell <sbartell at uci.edu>
License: GPL-3
NeedsCompilation: no
Materials: ChangeLog
CRAN checks: MapGAM results

Downloads:

Reference manual: MapGAM.pdf
Package source: MapGAM_0.7-0.tar.gz
MacOS X binary: MapGAM_0.7-0.tgz
Windows binary: MapGAM_0.7-0.zip
Old sources: MapGAM archive