View source: R/get_optimality.R
| get_optimality | R Documentation |
Returns a list of optimality values (or one value in particular).
Note: The choice of contrast will effect the G efficiency value, and gen_design()
and eval_design() by default set different contrasts (contr.simplex() vs contr.sum).
get_optimality(output, optimality = NULL, calc_g = FALSE)
output |
The output of either |
optimality |
Default |
calc_g |
Default |
A dataframe of optimality conditions. D, A, and G are efficiencies (value is out of 100).
T is the trace of the information matrix, E is the minimum eigenvalue of the information matrix,
I is the average prediction variance, and Alias is the trace of the alias matrix.
# We can extract the optimality of a design from either the output of `gen_design()`
# or the output of `eval_design()`
factorialcoffee = expand.grid(cost = c(1, 2),
type = as.factor(c("Kona", "Colombian", "Ethiopian", "Sumatra")),
size = as.factor(c("Short", "Grande", "Venti")))
designcoffee = gen_design(factorialcoffee, ~cost + size + type, trials = 29,
optimality = "D", repeats = 100)
#Extract a list of all attributes
get_optimality(designcoffee)
#Get just one attribute
get_optimality(designcoffee,"D")
# Extract from `eval_design()` output
power_output = eval_design(designcoffee, model = ~cost + size + type,
alpha = 0.05, detailedoutput = TRUE)
get_optimality(power_output)
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