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 published 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
value could not have occurred to due the effects of sampling error alone.
Alternatively, if a replication effect size falls within the replication
interval then the replication results could have reasonably occurred due to
the effects of sampling error alone. This package has functions that
calculate the replication interval for two different types of effect sizes,
namely correlation (i.e., r) and the standardized mean difference
(i.e.,d-value).

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 published 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
value could not have occurred to due the effects of sampling error alone.
Alternatively, if a replication effect size falls within the replication
interval then the replication results could have reasonably occurred due to
the effects of sampling error alone. This package has functions that
calculate the replication interval for two different types of effect sizes,
namely correlation (i.e., r) and the standardized mean difference
(i.e., d-value).

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.