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.
rrcalc(object, rrunit = 1)
Unit of relative risk.
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.
The results of "<Threshold" mean that the relative risk and 95% confidence interval when the exposure increases by
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)
Youn-Hee Lim, Il-Sang Ohn, and Ho Kim
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# 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)