ri.r.demo

(optional) Replication study: Sample size. If not specified, n is used.

rep.n

All samples are drawn from a common population. This specifies the population correlation.

Indicate the number of pairs of sample (original, replication) that should be used. 10,000 or higher suggested for stable results.

number.trials

(optional 0 to 1 value) Probability level desired (0 to 1). If not specified .95 (i.e., 95 percent) will be used.

prob.level

Apply bias correction formula to d-values.

bias.correction


Simulation to demonstrate the meaning of the correlation replication interval


A common problem faced by journal reviewers and authors is the question of
whether the results of a replication study are consistent with the original
published study. One solution to this problem is to examine the effect size
from the original study and generate the range of effect sizes that could
reasonably be obtained (due to random sampling) in a replication attempt
(i.e., calculate a replication interval). If a replication effect size falls
outside the replication interval, then that effect likely did not occur
due to the effects of sampling error alone. Alternatively, if a replication
effect size falls within the replication interval, then the replication
effect could have reasonably occurred due to the effects of sampling error
alone. This package has functions that calculate the replication interval for
the correlation (i.e., r), standardized mean difference (i.e., d-value), and mean.
The calculations used in version 2.0.0 and onward differ from past calculations
due to feedback during the journal review process. The new calculations allow
for a more precise interpretation of the replication interval.

ri.r.demo: Simulation to demonstrate the meaning of the correlation replication interval

Description

Usage

Arguments

Value

Examples