Description Usage Arguments Details Value Note Author(s) References Examples
View source: R/safeguard.d.CI.r
These functions are meant to help the researcher in the exploration of different scenarios when planning a replication study. Starting from the original sample size and effect size and from a feasible sample size for the replication study, these functions allow to identify the corresponding safeguard confidence level at a given power and alpha level.
1 2 |
d |
Standardized mean difference, Cohen's d |
r |
Pearson's correlation coefficient |
n |
Sample size of the original study |
n.1 |
Sample size for group 1 of the original study |
n.2 |
Sample size for group 2 of the original study |
nrep |
Sample size of the replication study. The functions assume two equal samples for the replication, therefore an even number is expected. |
sig.level |
Significance level (Type I error probability or alpha) |
power |
Power of the test (1 minus Type II error probability or 1 minus beta) |
Function safeguard.d.CI
and safeguard.r.CI
compute the safeguard confidence interval that corresponds to a sample size for the replication study (nrep
), at a certain level of power
and of sig.level
(Type I error), through a binary search. safeguard.d.CI takes the Cohen's d as input (assuming a two independent samples t-test), while safeguard.r.CI
takes the Pearson correlation coefficient as input.
CI
, an integer representing the (one-tailed) confidence interval is returned. The output is therefore in the interval .5 <= CI
<= 1.
The functions identify the CI corresponding to a certain value of the replication sample size (nrep
) through a binary search. A warning message is returned if the replication sample size nrep
is too small (i.e., not large enough even to meet the requirements of a standard power analysis): in this case a value of CI
= .5 is returned. If the value of CI
is too close to .5 or to 1 (i.e., a difference less than 10e-6), the binary search is stopped and a value of .5 or 1 respectively is returned, with a warning message.
Giulio Costantini (giulio.costantini@unimib.it)
Perugini, M., Gallucci, M., Costantini, G. (in preparation) Safeguard Power as a Protection Against Imprecise Power Estimates
1 2 3 4 5 | # example of function safeguard.d.CI
safeguard.d.CI(d = .8, n.1 = 30, n.2 = 30, nrep = 100)
# example of function safeguard.r.CI
safeguard.r.CI(r = .4, n = 30, nrep = 100)
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