> 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) [1] 0.9510506
The function "attributes" helped me figure this out.
hope this helps. spencer graves
Martin Biuw wrote:
Hello,
I've written a simple (although probably overly roundabout) function to test whether two regression slope coefficients from two linear models on independent data sets are significantly different. I'm a bit concerned, because when I test it on simulated data with different sample sizes and variances, the function seems to be extremely sensitive both of these. I am wondering if I've missed something in my function? I'd be very grateful for any tips.
Thanks!
Martin
TwoSlope <-function(lm1, lm2) {
## lm1 and lm2 are two linear models on independent data sets
coef1 <-summary(lm1)$coef coef2 <-summary(lm2)$coef
sigma <-(sum(lm1$residuals^2)+sum(lm2$residuals^2))/(lm1$df.residual + lm2$df.residual-4)
SSall <-sum(lm1$model[,2]^2) + sum(lm2$model[,2]^2)
SSprod <-sum(lm1$model[,2]^2) * sum(lm2$model[,2]^2)
F.val <-(as.numeric(coefficients(lm1)[2]) - as.numeric(coefficients(lm2) [2]))^2/((SSall/SSprod)*sigma)
p.val <-1-pf(F.val, 1, (lm1$df.residual + lm2$df.residual-4))
cat("\n\nTest for equality between two regression slopes\n\n") cat("\nCoefficients model 1:\n\n") print(coef1)
cat("\nCoefficients model 2:\n\n") print(coef2)
cat("\nF-value on 1 and", lm1$df.residual + lm2$df.residual-4, "degrees of freedom:" ,F.val, "\n")
cat("p =", ifelse(p.val>=0.0001, p.val, "< 0.0001"), "\n")
}
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