heat-package: Health Effects of Air pollution and Temperature (HEAT)
In HEAT: Health Effects of Air Pollution and Temperature (HEAT)

Description Details Author(s) See Also Examples

Package HEAT provides Korea data of mortality and environment variables for time-series analysis. The package includes several functions to read specific city information, generate single and moving average lag days, and estimate a threshold point in a nonlinear relationship.

Package:	HEAT
Type:	Package
Version:	1.2
Date:	2013-10-03
License:	GPL-2
LazyLoad:	yes

The package can be used to analyze Korea mortality and environment data, providing following functions: function read6city to load a single city's data, function lagdata to generate exposure variables at single and moving average lag days, function threshpt to estimate threshold point of a nonlinear relationship (e.g., U-, V-, or J-shape), function summary.threshpt to give summary informations for a fitted threshpt object, function plot.threshpt to produce some informative plots, and function rrcalc to calculate relative risks and their 95% confidence intervals below and above a threshold.

The package was supported by the Basic Science Research Program (#2010-0009581), International Research & Development Program (#2012K1A3A1A12054839), Women Scientist Research Program (#2012R1A1A3005549) and Global Research Lab (#K21004000001-10A0500-00710) through the National Research Foundation of Korea (NRF) funded by the Korea Ministry of Science, ICT (Information and Communication Technologies) and Future Planning.

Youn-Hee Lim, Il-Sang Ohn, and Ho Kim

Maintainer: Il-Sang Ohn <byeolbaragi@gmail.com>

read6city, lagdata, threshpt

# read the Seoul data set and create lag variables
data(mort)
seoul = read6city(mort, 11)
seoul_lag = lagdata(seoul, c("meantemp", "mintemp", "meanpm10", "meanhumi"), 5)

# find a optimal threshold and conduct piecewise linear regression
mythresh = threshpt(nonacc ~ meantemp_m3 + meanpm10_m2 +  meanhumi + ns(sn, 4*10) + factor(dow), 
			     expvar = "meantemp_m3", family = "poisson", data = seoul_lag,
			     startrng = 23, endrng = 33, searchunit = 0.2)

# provide summary informations
summary(mythresh)