To match events across observers for IOA, define the event boundary, sequence rule, time tolerance, and contextual identifiers before viewing the paired records. Apply the rule consistently and retain unmatched or ambiguous events. Similar durations or nearby timestamps alone can pair different events. Event matching should expose disagreement rather than maximize the final percentage.

Define event boundaries

Specify onset, offset, minimum separation, interruption, and whether clustered responses form one event or several.

Use multiple identifiers

Combine time, sequence, location, activity, and a neutral event ID when feasible.

Set the tolerance prospectively

Choose the time window before opening both records. Record the reason and version.

Route ambiguous matches

Keep an unresolved state and a qualified reviewer. Forced pairing hides event-detection disagreement.

Build a candidate-event ledger

Give every recorded event its own row. Retain observer, onset, offset, duration, sequence, location, activity, and the raw note or source pointer. Apply the predeclared tolerance and contextual rules to propose a match. A final match should be one-to-one. If one observer records a long episode while the other records two shorter episodes, keep the split or merge question visible for review.

The reviewer should see why each pair qualifies. A timestamp within tolerance may still describe a different response, and similar durations may occur in separate activities. Record matched, A-only, B-only, ambiguous, split, merged, and invalid states without deleting the original events.

Reconcile Dae's event states

Dae's five matched pairs contain ten observer records. Two A-only and one B-only record bring the observer-record total to thirteen, which agrees with seven records from A plus six from B. At the event-state level, five paired states plus three unmatched states produce eight unique states. Both reconciliations should appear in the worksheet.

Useful descriptive matching views include 5 of 8 unique states paired, or 62.5%, 5 of 7 A records paired, or 71.4%, and 5 of 6 B records paired, or 83.3%. These percentages describe event matching coverage. They are not a substitute for the selected IOA calculation. Duration-per-occurrence agreement, for example, can be computed only across the five paired events and must retain the unmatched-event counts beside it.

Resolve ambiguity without tuning the score

Apply the same rule across every record before looking at the final percentage. If a qualified reviewer resolves an ambiguous pair, preserve the original state, decision, reason, and date. A sensitivity summary can show how the result changes when uncertain pairs are included or excluded. This makes the judgment visible and prevents a matching rule from being tightened or relaxed merely to improve agreement.

Apply the field control to one defined question

The event-matching table for Dae begins with the exact decision, the responsible qualified role, and the evidence needed. Preserve original observer records, matched exposure, the selected calculation, raw numerator and denominator, unrounded result, and every excluded or unresolved unit.

Work the example for Dae

Dae's Observer A records seven events and Observer B records six. The predeclared rule yields five matched pairs, two A-only events, and one B-only event. Keep all eight unique event states visible. Duration-per-occurrence IOA can use the five pairs while unmatched events remain a separate result.

Audit the denominator for Dae

The denominator for Dae is the eligible cohort defined before review. Report planned, due, observed, matched, invalid, missing, and open units separately. A percentage gains meaning from the unit, coverage, dates, conditions, and disagreement pattern.

Protect access and safety during the sample for Dae

The observation for Dae keeps AAC, interpreters, mobility, food, water, bathroom use, prescribed care, health supports, rest, relationships, and emergency help available. Observer procedure never delays immediate safety or mandated action. Record changes in access, health, assent, distress, visibility, staff behavior, or routine.

Use current sources within their scope for Dae

For Dae, the BACB ethics hub points to current ethics materials. The CASP public summary supplies high-level autism-treatment scope. The BACB Ethics Code addresses competence, client involvement, consent and assent when applicable, documentation, supervision, risk, and evaluation for covered behavior analysts. The BCBA Test Content Outline includes measurement, reliability, sampling, and data-based decisions as examination content.

For Dae and the prospective event matching question, Vollmer, Sloman, and St. Peter Pipkin discuss practical implications of data reliability and treatment-integrity monitoring. Essig, Rotta, and Poling review IOA and fidelity reporting in an identified research corpus. Reed and Azulay describe agreement calculations and a calculation tool. ASHA says AAC users should always have access to their tools or devices. The responsible clinician still selects a case-specific measurement and review plan.

Close the IOA review for Dae

Review the event-matching table with Dae through accessible communication and with the responsible clinician. Record the question, sample, method, arithmetic, disagreement types, limits, repair, owner, next observation, and review date. Reopen the review when the definition, observer, setting, system, exposure, access, prevalence, procedure, or decision changes.

Before closing, confirm that each raw observer record appears once in the ledger, each final match is one-to-one, and every unmatched or ambiguous event has a disposition. Check that event-matching coverage and the selected IOA measure remain separately labeled.

Related resources

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