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Contrasts in Aniva

I understand the contrasts from previous posts, and I think I'm doing the right thing, but that does not give me what I would expect.

x <- c(11.80856, 11.89269, 11.42944, 12.03155, 10.40744, 12.48229, 12.1188, 11.76914, 0, 0, 13.65773, 13.83269, 13.2401, 14.54421, 13.40312) type <- factor(c(rep("g",5),rep("i",5),rep("t",5))) type [1] gggggiiiiittttt Levels: git

When I ran this:

 > summary.lm(aov(x ~ type)) Call: aov(formula = x ~ type) Residuals: Min 1Q Median 3Q Max -7.2740 -0.4140 0.0971 0.6631 5.2082 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 11.514 1.729 6.659 2.33e-05 *** typei -4.240 2.445 -1.734 0.109 typet 2.222 2.445 0.909 0.381 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 3.866 on 12 degrees of freedom Multiple R-squared: 0.3753, Adjusted R-squared: 0.2712 F-statistic: 3.605 on 2 and 12 DF, p-value: 0.05943

Here, my link is my type "g", so my typei is the difference between type "g" and type "i", and my typet is the difference between type "g" and type "t" typet

I wanted to see two more contrasts: the difference between typei+typeg and type "t" and the difference between type "i" and type "t"

therefore contrasts

 > contrasts(type) <- cbind( c(-1,-1,2),c(0,-1,1)) > summary.lm(aov(x~type)) Call: aov(formula = x ~ type) Residuals: Min 1Q Median 3Q Max -7.2740 -0.4140 0.0971 0.6631 5.2082 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 10.8412 0.9983 10.860 1.46e-07 *** type1 -0.6728 1.4118 -0.477 0.642 type2 4.2399 2.4453 1.734 0.109 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 3.866 on 12 degrees of freedom Multiple R-squared: 0.3753, Adjusted R-squared: 0.2712 F-statistic: 3.605 on 2 and 12 DF, p-value: 0.05943

When I try to make a second contrast by changing my link, I get different results. I do not understand what is wrong with my contrast.

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Refence: http://www.ats.ucla.edu/stat/r/library/contrast_coding.htm

 mat <- cbind(rep(1/3, 3), "g+i vs t"=c(-1/2, -1/2, 1),"i vs t"=c(0, -1, 1)) mymat <- solve(t(mat)) my.contrast <- mymat[,2:3] contrasts(type) <- my.contrast summary.lm(aov(x ~ type)) my.contrast > g+i vs ti vs t [1,] -1.3333 1 [2,] 0.6667 -1 [3,] 0.6667 0 > contrasts(type) <- my.contrast > summary.lm(aov(x ~ type)) Call: aov(formula = x ~ type) Residuals: Min 1Q Median 3Q Max -7.274 -0.414 0.097 0.663 5.208 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 10.841 0.998 10.86 1.5e-07 *** typeg+i vs t 4.342 2.118 2.05 0.063 . typei vs t 6.462 2.445 2.64 0.021 * --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 3.87 on 12 degrees of freedom Multiple R-squared: 0.375, Adjusted R-squared: 0.271 F-statistic: 3.6 on 2 and 12 DF, p-value: 0.0594
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