# cmatbd

##### Computes the treatment information matrix

The function `cmatbd`

computes the information matrix (C-matrix) for treatment effects under either the linear fixed effects model or the linear mixed effects model setting for a given block design of size 2.

- Keywords
- information matrix, C-matrix

##### Usage

`cmatbd(trt.N, blk.N, theta, des)`

##### Arguments

- trt.N
integer, specifying number of treatments,

`v`

.- blk.N
integer, specifying number of blocks,

`b`

.- theta
numeric, representing function of the ratio of random block variance and random error variance. It takes any value between 0 and 1, inclusive.

- des
matrix, a

`2 x b`

block design with`b`

blocks of size`k = 2`

and`v`

treatments.

##### Value

Returns a `v x v`

treatment information matrix (C-matrix).

##### References

Debusho, L. K., Gemechu, D. B. and Haines, L. (2018). Algorithmic construction of optimal block designs for two-colour cDNA microarray experiments using the linear mixed effects model. *Communications in Statistics - Simulation and Computation, https://doi.org/10.1080/03610918.2018.1429617*.

Gemechu D. B., Debusho L. K. and Haines L. M. (2014). A-optimal designs for two-colour cDNA microarray experiments using the linear mixed effects model. *Peer-reviewed Proceedings of the Annual Conference of the South African Statistical Association for 2014 (SASA 2014), Rhodes University, Grahamstown, South Africa*. pp 33-40, ISBN: 978-1-86822-659-7.

##### See Also

##### Examples

```
# NOT RUN {
##Information matrix
trt.N <- 3
blk.N <- 3
theta <- 0.2
des <- intcbd(trt.N = 4, blk.N = 3)
cmatbd(trt.N, blk.N, theta, des)
# }
```

*Documentation reproduced from package Boptbd, version 1.0.5, License: GPL-2*