Tests all pairwise comparisons or comparisons with control for general block designs. Two single step asymptotic \(k\)-FWER (generalized family-wise error rate) controlling procedures are available: asymptotic Monte Carlo (AMC) and nonparametric bootstrap (NB).

*This function is deprecated and will be removed in a future release.*

## Usage

```
el_pairwise(
formula,
data,
control = NULL,
k = 1L,
alpha = 0.05,
method = c("AMC", "NB"),
B,
nthreads = 1L,
maxit = 10000L,
abstol = 1e-08
)
```

## Arguments

- formula
An object of class

`formula`

(or one that can be coerced to that class) for a symbolic description of the model to be fitted. It must specify variables for response, treatment, and block as 'response ~ treatment | block'. Note that the use of vertical bar (|) separating treatment and block.- data
A data frame, list or environment (or object coercible by

`as.data.frame()`

to a data frame) containing the variables in`formula`

.- control
An optional single character that specifies the treatment for comparisons with control.

- k
A single integer for \(k\) in \(k\)-FWER. Defaults to 1.

- alpha
A single numeric for the overall significance level. Defaults to

`0.05`

.- method
A single character for the procedure to be used; either

`AMC`

or`NB`

is supported. Defaults to`AMC`

.- B
A single integer for the number of Monte Carlo samples for the AMC (number of bootstrap replicates for the NB).

- nthreads
A single integer for the number of threads for parallel computation via OpenMP (if available). Defaults to

`1`

.- maxit
A single integer for the maximum number of iterations for constrained minimization of empirical likelihood. Defaults to

`10000`

.- abstol
A single numeric for the the absolute convergence tolerance for optimization. Defaults to

`1e-08`

.

## References

Kim E, MacEachern SN, Peruggia M (2023).
“Empirical Likelihood for the Analysis of Experimental Designs.”
*Journal of Nonparametric Statistics*.
doi:10.1080/10485252.2023.2206919
.

## Examples

```
if (FALSE) {
# All pairwise comparisons
data("clothianidin")
el_pairwise(clo ~ trt | blk, data = clothianidin, B = 1000)
# Comparisons with control
el_pairwise(clo ~ trt | blk,
data = clothianidin, control = "Naked", method = "NB", B = 500
)
}
```