Uses Rule 7 from Rainey (2026). The SE and sample size from an existing study are used to predict the SE of the planned study.
Arguments
- se_existing
Standard error from the existing study.
- n_existing
Respondents per condition in the existing study.
- interaction
Logical; TRUE for a 2x2 factorial interaction. The SE computation is unchanged (the existing SE already encodes the design), but totals, design labels, and manuscript sentences will reflect the factorial structure.
Examples
from_existing(se_existing = 1.8, n_existing = 268) |>
find_mde(n_planned = 500)
#> -- Power Analysis ------------------------------------------------------
#> Design: balanced, between-subjects
#> Source: existing study
#> CI level: 90% (size-0.05 test of directional hypothesis)
#>
#> Inputs:
#> SE (existing) = 1.8
#> n (existing) = 268 per condition
#> n (planned) = 500 per condition (1,000 total)
#>
#> Predicted SE = sqrt(268 / 500) * 1.8 = 1.32 [Rule 7]
#> MDE (80% power) = 2.49 * 1.32 = 3.28 [Rule 5]
#> MDE (95% power) = 3.29 * 1.32 = 4.34 [Rule 5]
#>
#> -- Manuscript sentence (edit as needed) --------------------------------
#> For a balanced, between-subjects design with 500 respondents per
#> condition (1,000 total) replicating an existing study with a standard
#> error of 1.8 (268 per condition), the predicted standard error is
#> 1.32. Using a one-sided test at the 0.05 level, the experiment has 80%
#> power to detect a treatment effect of 3.28 units and 95% power to
#> detect a treatment effect of 4.34 units.
#>
#> Note: The paper rounds the MDE factor to 2.5 for 80% power and 3.3 for
#> 95% power. This software uses exact values (2.49 and 3.29), so results
#> differ slightly from hand calculations using the rounded factors.