CAgrid

An evenly-spaced grid of prediction points approximately 5km apart that extended across the latitude and longitude coordinates of participants' locations throughout California with over 7,500 points. Areas with sparse population data are clipped.

datasets

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

CAgrid function

A data frame with 7579 geolocations.<dl>
 <dt><code>X</code></dt>
<dd>projected X coordinate.</dd> <dt><code>Y</code></dt>
<dd>projected Y coordinate.</dd> 
</dl>

Format

A Grid on State of California — CAgrid

A data frame with 7579 geolocations.<dl>
 <dt><code>X</code></dt>
<dd>projected X coordinate.</dd>

 <dt><code>Y</code></dt>
<dd>projected Y coordinate.</dd>

 
</dl>

CAgrid: A Grid on State of California

Description

Usage

Arguments

Format

Examples