od.eq.2group {anomo} | R Documentation |
Optimal sample allocation calculation for equivalence test of two-group means
Description
The optimal design of single-level experiments detecting
equivalence of two-group means is to choose the optimal sample
allocation that minimizes the variance of a treatment effect under
a fixed budget, which is approximately the optimal
sample allocation that maximizes statistical power under a fixed budget.
The optimal design parameter is
the proportion of individuals to be assigned to treatment (p
).
Usage
od.eq.2group(
p = NULL,
r12 = NULL,
c1 = NULL,
c1t = NULL,
m = NULL,
plots = TRUE,
plim = NULL,
varlim = NULL,
plab = NULL,
varlab = NULL,
vartitle = NULL,
verbose = TRUE
)
Arguments
p |
The proportion of individuals to be assigned to treatment. |
r12 |
The proportion of outcome variance explained by covariates. |
c1 |
The cost of sampling one unit in the control condition. |
c1t |
The cost of sampling one unit in the treated condition. |
m |
Total budget, default value is the total costs of sampling 600 individuals across treatment conditions. |
plots |
Logical, provide variance plots if TRUE, otherwise not; default value is TRUE. |
plim |
The plot range for p, default value is c(0, 1). |
varlim |
The plot range for variance, default value is c(0, 0.05). |
plab |
The plot label for |
varlab |
The plot label for variance, default value is "Variance". |
vartitle |
The title of variance plot, default value is NULL. |
verbose |
Logical; print the value of |
Value
Unconstrained or constrained optimal sample allocation (p
).
The function also returns function name, design type,
and parameters used in the calculation.
Examples
# Unconstrained optimal design #---------
myod <- od.eq.2group(r12 = 0.5, c1 = 1, c1t = 50)
myod$out # output