Hedges g From t Statistic Converter
Independent equal variance pool edt→Hedgesgwith approximateJ=1−3/(4df−1), n1, n2≥2. Not paired/Welcht, exact gamma correction or significance. Actual independently qualified instrument/cohort/matching units; no diagnosis, causal outcome, validated personal prediction or universal clinical cutoff.
Description
Hedges' g adjusts an independent-group standardized contrast for sample-size bias.
Hedges' g adjusts an independent-group standardized contrast for sample-size bias.1
Converting a pooled t statistic assumes equal variances and the applicable independent-group design. The calculation and input requirements are explained below.
When to use Hedges g From t Statistic Converter
Enter finite pooled independent-groups t and integer sample sizes 2–1000000.
How to use Hedges g From t Statistic Converter 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 Hedges g From t Statistic Converter.
- 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 |
|---|---|---|---|
| actualPooledIndependentT | Actual Pooled Independent T. Use the units and matching context stated in the calculation below. | number | Required; finite; other constraints below |
| firstSampleSize | First Sample Size. Use the units and matching context stated in the calculation below. | number | Required; integer 1–1000000; finite; other constraints below |
| secondSampleSize | Second Sample Size. Use the units and matching context stated in the calculation below. | number | Required; integer 1–1000000; finite; other constraints below |
Enter finite pooled independent-groups t and integer sample sizes 2–1000000. Set df=n1+n2-2 and apply the approximate correction 1-3/(4df-1) to t*sqrt(1/n1+1/n2). Paired and Welch designs are outside this branch.
g=(1-3/(4*(n1+n2-2)-1))*t*sqrt(1/n1+1/n2) 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": {
"actualPooledIndependentT": 2,
"firstSampleSize": 20,
"secondSampleSize": 20
},
"output": {
"result": {
"value": 0.6198901903376426
}
}
}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 Cliff Delta Nonoverlap Calculator for a complementary operation: Cliff's delta compares all cross-group observation pairs.
Use Common Language Effect Size Calculator for a complementary operation: Common-language effect size summarizes cross-group pairwise superiority.
References
-
Hedges g From t Statistic Converter — tool.io
Similar or alternative tools
- Cliff Delta Nonoverlap Calculator
Cliff's delta compares all cross-group observation pairs.
- Common Language Effect Size Calculator
Common-language effect size summarizes cross-group pairwise superiority.