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Observer Onset Tolerance Match

Compare two observers’ recorded event onsets using an explicitly inclusive time tolerance.

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Description

Compare supplied observer-onset disagreement with a tolerance.

Behavioral records distinguish observed outcomes, missing observations, response deadlines, code conflicts and sampling opportunities. Unobserved trials differ from observed wrong responses, while time coverage differs from event probability. Supplied observations and cutoff values do not by themselves validate a task or identify a behavioral mechanism.

Compare supplied observer-onset disagreement with a tolerance.

When to use this tool

Use Observer Onset Tolerance Match when you already have firstOnsetSeconds, secondOnsetSeconds, toleranceSeconds and need to compare supplied observer-onset disagreement with a tolerance.

How to use the tool and how it works

  1. Enter firstOnsetSeconds, secondOnsetSeconds, toleranceSeconds. Use the units and conventions below.
  2. Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
  3. Read absoluteGapSeconds, withinTolerance. Inspect withinTolerance before interpreting the associated values.

Require toleranceSeconds>=0; return abs(first-second) and absolute gap<=tolerance.1

Input fieldMeaning and unitsAccepted input
firstOnsetSecondsFirst Onset SecondsRequired. Finite number.
secondOnsetSecondsSecond Onset SecondsRequired. Finite number.
toleranceSecondsTolerance SecondsRequired. Finite number; minimum 0.
Output fieldInterpretationReturned shape
absoluteGapSecondsAbsolute Gap SecondsRequired. Finite number.
withinToleranceWithin ToleranceRequired. Boolean.
json
{
  "input": {
    "firstOnsetSeconds": 10,
    "secondOnsetSeconds": 10.2,
    "toleranceSeconds": 0.3
  },
  "output": {
    "absoluteGapSeconds": 0.1999999999999993,
    "withinTolerance": true
  }
}

Limitations and assumptions

  • Equality passes the stated tolerance. This does not establish independent observations, clock alignment, inter-rater reliability or appropriate tolerance.
  • Inputs must satisfy both the field types and the cross-field conditions above. Invalid input causes an error; a successful false flag or documented placeholder is a different result.
  • Numeric calculations use binary floating point unless exact decimal-integer arithmetic is explicitly stated. No hidden measurement tolerance or decimal rounding is added; nonfinite or out-of-contract results are rejected. Numeric signed-zero results are exported as zero.

Alternative or Complementary methods

Use the complete protocol, observation records and analysis plan. Check missingness, coding rules, timing and sampling design before interpreting local counts, labels or interval fractions as research outcomes or appropriate interventions.

References

  1. Calculation and input contract: behavioral-science/observer-onset-tolerance-match — tool.io

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