HEAT (version 1.2)

rrcalc: Estimation of relative risk

Description

rrcalc caculates relative risks below and above a threshold. Relative risks and the 95% C.I.s of lower unit and upper unit based on the threshold are estimated.

Usage

rrcalc(object, rrunit = 1)

Arguments

object

a fitted threshpt object produced by threshpt().

rrunit

Unit of relative risk.

Value

• The results of "rrunit below threshold. The results of ">=Threshold" mean those when the exposure increases by rrunit above threshold. RR = exp(beta*rrunit) and 95% C.I = exp((beta-1.96*s.e(beta), beta+1.96*s.e(beta))*rrunit)

Details

In GLM with log link, the coefficients of the exposure are equal to log values of RR. rrcalc gives relative risks in log link GLM, particularly, Poisson regression model.

Examples

# 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)


# calculate relative risks
rrcalc(mythresh)