Measurement and analysis are two of the fundamental components to an applied behavior analytic (ABA) intervention program. Measurement allows practitioners to demonstrate client progress, support treatment dosage recommendations, and provide an objective picture of a client’s present level of performance. Analysis occasions data-based decision making, problem solving, and the selection of treatment goals.

The primary goals of a behavior analytic program are to:

  • Maximize client happiness and quality of life
  • Increase the rate of skill acquisition
  • Minimize the gap in skills between clients and their same-aged peers

To do this, behavior analysts need to be as efficient and effective in their intervention design as possible. All too often, a clinician’s primary focus is on the individual skills in the client’s program (micro-level measures). By “zooming out” and applying a multi-tiered approach to measurement and analysis, practitioners can supercharge their clients’ programs.

Morningside Academy’s multi-tiered model of assessment provides an excellent and easily organized approach to evaluating skill development. This model incorporates three levels of assessment: macro, meta, and micro-level (Johnson & Street, 2004). These measures are categorized by both the frequency of implementation and the function of the actual measure (Johnson & Street, 2004).

Applying this multi-tiered framework to intensive behavior analytic intervention allows practitioners to continually evaluate the effectiveness of their intervention programs (Kubina, 2019), including the following:

  • Overall treatment effectiveness
  • Appropriateness of total treatment dosage
  • Rate of skill acquisition

Utilizing this measurement framework also supports practitioners in illustrating client progress to caregivers and other practitioners, rationalizing the need for increases/decreases in treatment dosage, and developing comprehensive treatment plans.

Micro-Level Data

Micro-level data are the ‘day-to-day’ session data – essentially the smallest, most frequent form of measurement. These give us a very specific view of client performance on each individual skill or behavior. Micro-level data are collected within each intervention session on each skill targeted for intervention (Johnson & Street, 2004; Kubina 2019).

Benefits of Micro-Level Data

These data are excellent for:

  • Reporting progress on a specific skill
  • Predicting or suggesting upcoming or next skills
  • Identifying trends in client’s performance that can benefit the client over time

Examples of micro-level data:

Micro-Level Measures
Mand for items
Remain calm during frustrating situations
Increase frequency of age-appropriate social interactions
Parent training: implementing adaptive routines at home

Meta-Level Data

Meta-level data provide “bigger picture” data, namely how the client is performing with respect to composite (more complex, related) skills or within repertoires. These data allow the practitioner to evaluate client progress over a period of time. Meta-level data are collected less frequently than micro-level data, typically weekly, monthly, or quarterly (Johnson & Street, 2004; Kubina 2019).

Benefits of Meta-Level Data

  • Provide an easily understandable “snapshot” of client progress on a skill
  • Evaluate client progress toward composite (complex) skills or repertoires Evaluate generativity and generalization
  • Identify missing component (prerequisite) skills, or “gaps” in the client’s learning
  • Alert practitioners to problem solve when progress is not being demonstrated at an appropriate rate or level
  • Alert practitioners when a client is ready to make move more quickly through the intervention program

Examples of tying meta-level data to micro-level data.

(Note- there are many measures listed here, to provide a variety of examples of meta-level measures. Clinicians could implement one or more of these measures, as contextually appropriate for the client and intervention program).

Macro-Level Measurement

Macro data assess larger shifts across behavioral repertoires. These data often norm-referenced, which allow practitioners to compare the performance of a client to that of other same-aged peers. These measures are implemented on an once or twice-yearly schedule (Johnson & Street, 2004; Kubina 2019).

Benefits of Macro-Level Data

  • Identify shifts in client’s developmental trajectory
  • Evaluate rate of progress over time
  • Frames a client’s skill level in relation to other repertoires
  • Allows practitioners to identify meaningful, and significant improvements in client progress

Examples of three-tiered measurement:

By “zooming out” and leveraging multi-tiered measurement for clinical programming, behavior analysts can take steps to become as efficient and effective in their intervention design as possible. Try applying a multi-tiered approach to your measurement, analysis and behavioral intervention, to supercharge your clients’ programs!


About the Author

Kristin Smith, M.Ed., BCBA, LBA is a Licensed Behavior Analyst, and Board Certified Behavior Analyst. She began her career in the field of behavior analysis in 2002 and received a master’s degree in Special Education from the University of Washington. Kristin has experience implementing and designing intervention programs across a variety of contexts, with learners ranging in age from 18 months to 40 years. She works with a wide variety of learners, including, but not limited to those with autism, chromosomal deletions, cognitive impairments, learning disabilities, social-emotional and/or behavioral problems, significant challenging behavior, blindness, and children with multiple disabilities. Her areas of expertise include Precision Teaching, instructional design, assessment, and data analysis.