DF <- data.frame(a=rep(letters[1:4], 2), y=1:8) > DF$b <- ((DF$a %in% letters[1:2])-(DF$a%in% letters[3:4])) > fit <- lm(y~b+a, DF, singular.ok=T) > summary(fit)
Call: lm(formula = y ~ b + a, data = DF, singular.ok = T)
Residuals: 1 2 3 4 5 6 7 8 -2 -2 -2 -2 2 2 2 2
Coefficients: (1 not defined because of singularities)
Estimate Std. Error t value Pr(>|t|) (Intercept) 4.500 1.414 3.182 0.0335 *
b -1.500 1.414 -1.061 0.3486 ab 1.000 2.828 0.354 0.7415 ac -1.000 2.828 -0.354 0.7415 ad NA NA NA NA ---
Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1
Residual standard error: 2.828 on 4 degrees of freedom Multiple R-Squared: 0.2381, Adjusted R-squared: -0.3333 F-statistic: 0.4167 on 3 and 4 DF, p-value: 0.751
This will give you what you want ONLY if you have the same number of observations in the two subsets to be compared. If not, then you can redefine DF$b to produce what you want.
hope this helps. spencer graves
Kimberly Ann Fernandes wrote:
Hello,
I am trying to figure out how to conduct a t-test on a specific contrast for my data. I have four factors in my data and would like to conduct a t-test on the average of the data from the first two factors against the average of the data on the second two factor (i.e. is the average of the first two different from the average of the second two). Is there a quick way to do this? I found the contrast function, but wasn't sure how to apply it.
Thank you, Kim
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