Description Usage Arguments Value Examples
Useful for assessing efficiency gains that might be achieved with a pooling design.
1 2 3 4 |
g |
Numeric vector of pool sizes to include. |
d |
Numeric value specifying true difference in group means. |
mu1, mu2 |
Numeric value specifying group means. Required if
|
sigsq |
Numeric value specifying the variance of observations. |
sigsq1, sigsq2 |
Numeric value specifying the variance of observations for each group. |
sigsq_p |
Numeric value specifying the variance of processing errors. |
sigsq_m |
Numeric value specifying the variance of measurement errors. |
multiplicative |
Logical value for whether to assume multiplicative rather than additive errors. |
alpha |
Numeric value specifying type-1 error rate. |
beta |
Numeric value specifying type-2 error rate. |
assay_cost |
Numeric value specifying cost of each assay. |
other_costs |
Numeric value specifying other per-subject costs. |
labels |
Logical value. |
Plot of power vs. total costs generated by
ggplot
.
1 2 3 4 5 6 7 8 9 10 | # Plot power vs. total study costs for d = 0.25, sigsq = 1, and costs of $100
# per assay and $0 in other per-subject costs.
poolpower_t(d = 0.5, sigsq = 1, assay_cost = 100, other_costs = 0)
# Repeat but with $10 in per-subject costs.
poolpower_t(d = 0.5, sigsq = 1, assay_cost = 100, other_costs = 10)
# Back to no per-subject costs, but with processing and measurement error
poolpower_t(d = 0.5, sigsq = 1, sigsq_p = 0.2, sigsq_m = 0.1,
assay_cost = 100, other_costs = 0)
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