MapGAM: Mapping Smoothed Effect Estimates from Individual-Level Data

Contains functions for mapping odds ratios, hazard ratios, or other effect estimates using individual-level data such as case-control study data, using generalized additive models (GAMs) or Cox models for smoothing with a two-dimensional predictor (e.g., geolocation or exposure to chemical mixtures) while adjusting linearly for confounding variables, using methods described by Kelsall and Diggle (1998), Webster at al. (2006), and Bai et al. (submitted). Includes convenient functions for mapping point estimates and confidence intervals, 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).

AuthorLu Bai, Scott Bartell, Robin Bliss, and Veronica Vieira
Date of publication2016-09-03 16:39:06
MaintainerScott Bartell <sbartell@uci.edu>
LicenseGPL-3
Version1.0

View on CRAN

Functions

beertweets Man page
CAdata Man page
CAgrid Man page
CAmap Man page
colormap Man page
dls Man page
gamcox Man page
gamcox.fit Man page
MAdata Man page
MAmap Man page
MapGAM Man page
MapGAM-package Man page
MapGAM.version Man page
modgam Man page
mypredict.gam Man page
optspan Man page
plot.modgam Man page
predgrid Man page
predict.gamcox Man page
print.gamcox Man page
print.modgam Man page
sampcont Man page
toformula Man page
trimdata Man page

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