el_pairwise: Pairwise comparisons for general block designs

In melt: Multiple Empirical Likelihood Tests

Pairwise comparisons for general block designs

Description

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.

Value

A list with class c("pairwise", "melt").

References

Kim E, MacEachern SN, Peruggia M (2023). “Empirical Likelihood for the Analysis of Experimental Designs.” Journal of Nonparametric Statistics. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/10485252.2023.2206919")}.

Examples

## Not run: 
# 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
)

## End(Not run)

melt documentation built on May 31, 2023, 7:12 p.m.