Why the slope and intercept of 95% CI varies at each calculation when using package mcr?
Hello, I know nothing about package mcr but by reading the help page for function mcreg I conclude that CI's are calculated using a bootstrap resampling technique and therefore you should expect different values every time the function runs unless you set the random generator seed using ?set.seed. Hope this helps, Rui Barradas Em 26-02-2017 07:51, vod vos escreveu:
Hi Everybody,
aa<- c(1,5,10,20,50,40,50,60,70,80,90,100,150,200,250,300,350,400,450,500,550,600,650,700,750,800,850,900,950,1000)
bb<- c(8,16,30,24,39,54,40,68,72,62,122,80,181,259,275,380,320,434,479,587,626,648,738,766,793,851,871,957,1001,960)
library(mcr)
pbreg<- mcreg(aa,bb, method.reg = "PaBa")
pbreg at para
EST SE LCI UCI
Intercept 7.081869 NA -2.824761 20.169193
Slope 1.055312 NA 1.024968 1.096982
but when you calculate again,
pbreg<- mcreg(aa,bb, method.reg = "PaBa")
pbreg at para
EST SE LCI UCI
Intercept 7.081869 NA -1.834744 20.598912
Slope 1.055312 NA 1.025339 1.095888
pbreg at para show different values of LCI and UCI compared to the first time, how does this happen?
Thanks.
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