Hello R users, I've used the following help: > "Comparing two regression line slopes" > I knew the method based on the following statement : > t = (b1 - b2) / sb1,b2 > where b1 and b2 are the two slope coefficients and sb1,b2 the pooled > standard error of the slope (b) > > which can be calculated in R this way: > > df1 <- data.frame(x=1:3, y=1:3+rnorm(3)) > > df2 <- data.frame(x=1:3, y=1:3+rnorm(3)) > > fit1 <- lm(y~x, df1) > > s1 <- summary(fit1)$coefficients > > fit2 <- lm(y~x, df2) > > s2 <- summary(fit2)$coefficients > > db <- (s2[2,1]-s1[2,1]) > > sd <- sqrt(s2[2,2]^2+s1[2,2]^2) > > df <- (fit1$df.residual+fit2$df.residual) > > td <- db/sd > > 2*pt(-abs(td), df) Using my data I finally get the value of the test, which is: 2.245e-7. Do my slopes differ significantly now? Thanks for help, Benedikt
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