Posner Cueing Effect

Measure invalid-minus-valid Posner cueing benefit after correct-trial and caller-supplied RT-window exclusions; both conditions must remain observed.

Description

A cueing benefit compares correct response times after valid and invalid cues.

A cueing benefit compares correct response times after valid and invalid cues. Plausible-time filtering changes which observations contribute.

The tool returns validMeanMs (valid mean ms); invalidMeanMs (invalid mean ms); cueingBenefitMs (cueing benefit ms); includedTrialIndexes (included trial indexes). Input measurements and model parameters are supplied by the caller; the tool computes the stated summary rather than acquiring those measurements.

When to use Posner Cueing Effect

Use Posner Cueing Effect when you already have reactionTimesMs, validCueFlags, correctFlags, minimumReactionTimeMs, maximumReactionTimeMs and want validMeanMs, invalidMeanMs, cueingBenefitMs, includedTrialIndexes. This is useful for checking a supplied calculation, documenting a measurement convention, or comparing observations prepared on the same basis.

How to use Posner Cueing Effect and understand its results

Enter reactionTimesMs, validCueFlags, correctFlags, minimumReactionTimeMs, maximumReactionTimeMs 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 validMeanMs, invalidMeanMs, cueingBenefitMs, includedTrialIndexes. 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
reactionTimesMs	Reaction times ms	list of number	Required
validCueFlags	Valid cue flags	list of number	Required
correctFlags	Correct flags	list of number	Required
minimumReactionTimeMs	Minimum reaction time ms	number	Required
maximumReactionTimeMs	Maximum reaction time ms	number	Required

Include only correct trials within both supplied RT bounds, including endpoints. Require retained observations in each cue group and return their original zero-based indexes.

benefitMs = mean(invalid-cue RT)−mean(valid-cue RT)

The symbols refer to the supplied quantities or generated values described above; unit conversions and comparison boundaries follow the stated implementation.

json

{
  "input": {
    "reactionTimesMs": [
      200,
      250,
      300,
      400
    ],
    "validCueFlags": [
      1,
      1,
      0,
      0
    ],
    "correctFlags": [
      1,
      0,
      1,
      1
    ],
    "minimumReactionTimeMs": 100,
    "maximumReactionTimeMs": 500
  },
  "output": {
    "validMeanMs": 200,
    "invalidMeanMs": 350,
    "cueingBenefitMs": 150,
    "includedTrialIndexes": [
      0,
      2,
      3
    ]
  }
}

Limitations and assumptions

Filtering bounds and task labels are supplied. No outlier inference, uncertainty or attentional diagnosis occurs.

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

Visual Search Slope: Aggregate correct-trial visual-search RTs by set size and fit equally weighted condition means; signed slopes are retained and no serial/parallel search diagnosis is asserted. Stop Signal Reaction Time: Estimate integration-method SSRT using linearly interpolated go-RT quantiles and max-RT omission replacement; negative estimates are preserved and flagged, not validated as race-model compatible.

Methodological background: Measures of scale: sample variance and standard deviation.^[1]

References

Measures of scale: sample variance and standard deviation — NIST/SEMATECH

Similar or alternative tools

Visual Search Slope
Aggregate correct-trial visual-search RTs by set size and fit equally weighted condition means; signed slopes are retained and no serial/parallel search diagnosis is asserted.
Stop Signal Reaction Time
Estimate integration-method SSRT using linearly interpolated go-RT quantiles and max-RT omission replacement; negative estimates are preserved and flagged, not validated as race-model compatible.