bibdAOV

Computes a balanced incomplete block design [BIBD] analysis of variance.

This file computes a balanced incomplete block design [BIBD] analysis of variance. A BIBD is a set X of v >= 2 elements called treatments and a collection of b > 0 subsets of X, called blocks, such that the following conditions are satisfied:

- each block consists of exactly k treatments, v > k > 0
- each treatment appears in exactly r blocks, r > 0
- each pair of treatments appear simultaneously in exactly l (lambda) blocks, l > 0.

A BIBD must satisfy [constraits]:
v*r = b*k = eu = Total number of experimental units for whole experiment
r*[k-1] = l*[v-1])
The Linear Model is:
x_ij = µ + a_i + b_j + e_ij
i = 1,...,v (treatments); j = 1,...,a (blocks); e_ij ~ N[0,var_e]

It needs to input the data matrix (size of matrix must be n-by-3: data=column 1, treatment=column 2, block=column 3), and significance level (default = 0.05).

The output is a detailed balanced incomplete block esign analysis of variance table.