AIC.modgam

This function summarizes the AIC of a modgam object produced by <code>modgam</code>.

misc

smooth

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. (2020).  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).

Scott Bartell

MapGAM

Mapping Smoothed Effect Estimates from Individual-Level Data

AIC.modgam function

<dl> <dt>object</dt>
<dd>a modgam object.</dd> <dt>...</dt>
<dd>extra arguments for S3 generic, ignored by <code>AIC.modgam</code>.</dd></dl>

Arguments

Lu Bai
Send bug reports to <a href="/link/sbartell%40uci.edu?package=MapGAM&version=1.3" data-mini-rdoc="MapGAM::sbartell@uci.edu">sbartell@uci.edu</a>.

Author

AIC of the modgam Object — AIC.modgam

<dl>

 <dt>object</dt>
<dd>a modgam object.</dd>

 <dt>...</dt>
<dd>extra arguments for S3 generic, ignored by <code>AIC.modgam</code>.</dd>

</dl>

Lu Bai
Send bug reports to <a href='mailto:sbartell@uci.edu'>sbartell@uci.edu</a>.

AIC.modgam: AIC of the `modgam` Object

Description

Usage

Arguments

Author

See Also