Fail-Safe N File Drawer Calculator
Rosenthal fail-safeNformula(sumZ)²/zcritical²−kwith independently consistent one/two sided significance convention. Signed estimates retained, not publication bias proof or robust missing study inference. Actual independently qualified instrument/cohort/matching units; no diagnosis, causal outcome, validated personal prediction or universal clinical cutoff.
Description
Rosenthal's fail-safe N is a formula-based summary of study z-scores.
Rosenthal's fail-safe N is a formula-based summary of study z-scores.1
Its significance convention must be consistent, and the summary does not prove the absence of publication bias. The calculation and input requirements are explained below.
When to use Fail-Safe N File Drawer Calculator
Enter nonempty finite independent study z-scores and a positive matched normal critical value.
How to use Fail-Safe N File Drawer Calculator and how it works
- Prepare the measurements or independently established model inputs described below, with matching units and observation scope.
- Enter the required fields and run Fail-Safe N File Drawer Calculator.
- Read the result fields using the formula, output units, signs and ordering explained below.
- Correct any rejected inputs and rerun; interpret the result within the stated model and its assumptions.
| Input field | Meaning | Value type | Requirement |
|---|---|---|---|
| actualIndependentStudyZScores | Actual Independent Study Z Scores. Use the units and matching context stated in the calculation below. | array of number | Required; other constraints below |
| callerMatchedNormalCriticalValue | Caller Matched Normal Critical Value. Use the units and matching context stated in the calculation below. | number | Required; strictly positive; finite; other constraints below |
Enter nonempty finite independent study z-scores and a positive matched normal critical value. Square the summed z-score, divide by squared critical value and subtract study count. Negative estimates remain negative and are not rounded to a missing-study count.
failSafeN=(sum(zScores)/criticalZ)^2-studyCount Apply the input ordering, units and branch conditions stated above.
| Output field | Meaning | Value type |
|---|---|---|
| result | Object containing the calculated or selected fields below. | object |
| result.value | Numeric result under the formula and output units explained above. | number |
{
"input": {
"actualIndependentStudyZScores": [
1,
2
],
"callerMatchedNormalCriticalValue": 1.7320508075688772
},
"output": {
"result": {
"value": 1.0000000000000004
}
}
}Limitations and assumptions
The calculation uses the supplied observations and model inputs. It does not collect measurements, select a reference population or coefficient, or establish that the model applies to the actual case. The stated branch conditions and output units remain part of the result.
All fields require explicit values. Unexpected fields, wrong types, nonfinite numbers and sparse arrays are rejected. Alignment, bounds and supported-token rules are explained above; extremely large inputs or nonfinite results can also fail. Input errors differ from successful false comparisons, unavailable-domain flags and empty match lists.
Alternative or Complementary methods
Use Independent t-Test Power .80 Sample Size for a complementary operation: Two-group power planning requires a proposed effect and significance level.
Use SEM Minimum Sample 10-Per-Parameter Rule for a complementary operation: A participants-per-parameter heuristic is a nominal planning budget.
References
-
Fail-Safe N File Drawer Calculator — tool.io
Similar or alternative tools
- Independent t-Test Power .80 Sample Size
Two-group power planning requires a proposed effect and significance level.
- SEM Minimum Sample 10-Per-Parameter Rule
A participants-per-parameter heuristic is a nominal planning budget.