Glossary term

Momentary time sampling

Learn how momentary time sampling checks behavior at set instants, how to calculate results, and how interval length, missed checks, and brief responses matter.

5
min read
Updated
August 13, 2026
Sources checked
August 13, 2026
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Also called

momentary sampling MTS

How does momentary time sampling work? Momentary time sampling checks whether a defined response is occurring at a scheduled instant, often the end of each interval. Each valid checkpoint receives a yes or no score. The result is positive checks divided by completed checks. It describes sampled moments, while exact response count and total duration remain unknown.

The observer looks at one designated moment

For a 20-minute observation with one-minute intervals, a timer signals 20 checkpoints. At each signal, the observer looks and records whether the response is occurring under the written definition. Activity earlier in the interval does not affect that score.

This differs from partial-interval recording, which scores any occurrence during the interval, and whole-interval recording, which requires occurrence throughout the interval. The abbreviation MTS also appears in ABA for matching-to-sample tasks. The full page title identifies momentary time sampling here.

Build the schedule before observation

Define:

  • observation start and stop events
  • checkpoint spacing and timer source
  • response definition and observation window around the signal
  • eligible checks and exclusions
  • treatment of late, early, or missed checks
  • required communication, health, sensory, and mobility supports

A checkpoint quietly moved to a convenient moment becomes a different sample. If the observer looks too late, use the predeclared tolerance or mark it missed.

Calculate the sampled percentage

Suppose behavior is occurring at 9 of 15 valid checkpoints. The momentary time-sampling result is 9 divided by 15 times 100, or 60%.

Keep the numerator and denominator with the percentage. Nine of 15 and 90 of 150 both equal 60%, yet the second estimate reflects far more checkpoints. Also report completed checks divided by planned checks so missing observation stays visible.

A fictional community example

Jun is a fictional 16-year-old who wants to stay involved in a community theater rehearsal while choosing breaks when needed. With Jun, the team defines engagement as acting, handling assigned materials, watching the current rehearsal segment, or communicating about the activity. A chosen break is recorded as a separate valid state.

The observer plans 18 two-minute checkpoints. At 15 valid checks, Jun is engaged at nine, taking a chosen break at four, and waiting during a staff delay at two. Engagement is 9 of 15, or 60%. Planned-sample completion is 15 of 18, or 83.3%.

Three checks were missed while the observer handled a room-access problem. They remain missing and do not become negative scores for Jun. The three-state record also avoids treating chosen breaks or system delays as the same outcome.

Interval spacing affects the sample

Widely spaced checks reduce workload and can miss brief or clustered responses. Closely spaced checks increase observation demand and can create correlated samples of the same long episode. Choose spacing based on response duration, likely pattern, setting demands, and the precision needed.

Changing from 30-second to five-minute checks can change the estimate. Mark a new procedure version and avoid joining both percentages into one uninterrupted series without analysis.

Fixed and variable checkpoints serve different plans

Equal intervals make timing, training, and review straightforward. A variable or pre-randomized schedule can spread checks across less predictable moments. Either approach needs a stored schedule generated before observation. Observer convenience should not decide when a check occurs.

If a timer cue is audible or visible to the person, record that feature because it may change activity near the checkpoint. Keep the same timing method across comparisons or mark the new version. When observations cover only one activity or hour, label that sampling frame rather than generalizing to the whole day.

MTS does not estimate every dimension

A positive score cannot reveal how many responses occurred, when they began, or how long they lasted. A response that happens many times between checkpoints can receive zero positives. A long episode spanning several checks can receive several positives while representing one event.

Use event recording for exact count when feasible, duration for total time, and latency for time from a defined event to response onset. Momentary sampling fits questions about state at sampled instants when the likely error is acceptable.

Protect access and person-centered context

Keep AAC, interpreters, mobility and sensory supports, breaks, food, water, bathroom access, prescribed care, and emergency help available. Record the person’s chosen activity, communication, assent, dissent, and report of the experience beside observer scores.

The observation system should measure the environment too. Delayed materials, unavailable communication, unclear schedules, or missing staff supports can change what is possible at a checkpoint.

Review reliability and representativeness

Sample observer agreement across times, activities, partners, and response states. Track on-time checks, missed checks, device failures, exclusions, and scoring corrections. Agreement supports scoring consistency and cannot prove that checkpoints represent the whole day.

The current BACB BCBA Test Content Outline, Sixth Edition covers discontinuous measurement, interval recording, time sampling, reliability, validity, and representative procedure selection. It provides examination content and no universal interval length.

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