We can obtain the sum of squares of a contrast for a regression of degree $j$ by: $$ SSR_j=\frac{\left(\displaystyle\sum_{i=1}^{I} C_{ji}T_i\right)^2}{rK_j}, $$
where $I$ is the number of levels of the factor, $r$ is the number of repetitions, $C_{ji}$ is the $i$-th coefficient for the $j$-th regression degree, $T_i$ is the total (sum of repetitions) of the factor level and: $$ K_j=\displaystyle\sum_{i=1}^{I} C^2_{ji}. $$
This works good for the case where the factor levels have the same number of repetitions (balanced). How should I proceed to estimate the $SSR_j$ for the case I have:
- Means: 56.5000, 39.6667, 42.5000, 57.5833
- N: 5, 6, 5, 5
for the linear, quadratic and cubic trends?
