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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