Digit Memory Span
Score supplied digit-span trials by caller-defined successful-trial count per sequence length; this does not implement a licensed test or normative interpretation.
Description
Digit-span trials can be grouped by sequence length.
Digit-span trials can be grouped by sequence length. A supplied minimum number of correct trials defines which tested lengths qualify.
The tool returns qualifiedLengths (qualified lengths); maximumQualifiedSpan (maximum qualified span). Input measurements and model parameters are supplied by the caller; the tool computes the stated summary rather than acquiring those measurements.
When to use Digit Memory Span
Use Digit Memory Span when you already have sequenceLengths, correctFlags, minimumCorrectTrials and want qualifiedLengths, maximumQualifiedSpan. This is useful for checking a supplied calculation, documenting a measurement convention, or comparing observations prepared on the same basis.
How to use Digit Memory Span and understand its results
- Enter sequenceLengths, correctFlags, minimumCorrectTrials using the field table below. Match the units, ordering and data boundaries described in the calculation.
- Run the tool after checking the stated bounds and matching paired observations or categories. A malformed request gives a tool error rather than a usable measurement.
- Read qualifiedLengths, maximumQualifiedSpan. Use the calculation and interpretation below to distinguish amounts, ratios, signs and decision flags where applicable.
- Review the supplied parameters and assumptions before using the result in a report or comparing it with another observation.
| Input field | Meaning | Value type and bounds | Requirement |
|---|---|---|---|
| sequenceLengths | Sequence lengths | list of number | Required |
| correctFlags | Correct flags | list of number | Required |
| minimumCorrectTrials | Minimum correct trials | integer | Required |
Group positive integer lengths with binary correct flags and sort qualifying lengths. If none qualify, return maximum span zero.
qualified length = correct count at length ≥ minimumCorrect; span = greatest qualified length The symbols refer to the supplied quantities or generated values described above; unit conversions and comparison boundaries follow the stated implementation.
{
"input": {
"sequenceLengths": [
3,
3,
4,
4,
5,
5
],
"correctFlags": [
1,
1,
1,
1,
1,
0
],
"minimumCorrectTrials": 2
},
"output": {
"qualifiedLengths": [
3,
4
],
"maximumQualifiedSpan": 4
}
}Limitations and assumptions
The calculator does not implement a standardized administration or stopping protocol. Untested lengths and population norms are not inferred.
Numerical inputs must be finite. The tool checks its declared input shape and calculation constraints; those checks do not verify the quality, calibration or representativeness of the supplied observations.
Alternative or Complementary methods
Attentional Blink Magnitude: Compute T2 accuracy conditional on correct T1 by lag and subtract from a caller-selected baseline lag; preserves facilitation/negative deficits and does not infer a blink window. Reliable Change Index: Compute a practice-adjusted Jacobson–Truax reliable-change index from caller norms and criterion; not a diagnosis or a universal improvement cutoff.
Methodological background: The psychometric function: fitting, sampling, and goodness of fit.1
References
-
The psychometric function: fitting, sampling, and goodness of fit — Wichmann and Hill; Perception & Psychophysics
Similar or alternative tools
- Attentional Blink Magnitude
Compute T2 accuracy conditional on correct T1 by lag and subtract from a caller-selected baseline lag; preserves facilitation/negative deficits and does not infer a blink window.
- Reliable Change Index
Compute a practice-adjusted Jacobson–Truax reliable-change index from caller norms and criterion; not a diagnosis or a universal improvement cutoff.