Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Randomization tests for ABAB designs: comparing-data-division- specific and common distributions.

Rumen Manolov1, Antonio Solanas

  • 1Universidad de Barcelona, Barcelona, Spain. rrumenov13@ub.edu

Psicothema
|April 17, 2008
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A tutorial for software options to aid in assessing functional relations in single-case experimental designs.

Behavior research methods·2026
Same author

Videoconferencing Cognitive Behavioral Therapy for Panic Disorder in an Emergency Room in Mexico: A Multiple Baseline Design.

Journal of clinical psychology in medical settings·2026
Same author

Compassion focused therapy for self-stigma and shame in autism: a single case pre-experimental study.

Frontiers in psychiatry·2024
Same author

Type I error rates and power of two randomization test procedures for the changing criterion design.

Behavior research methods·2023
Same author

Cognitive Orientation to daily Occupational Performance to improve occupational performance goals for children with executive function deficits after acquired brain injury.

Developmental medicine and child neurology·2023
Same author

Testing delayed, gradual, and temporary treatment effects in randomized single-case experiments: A general response function framework.

Behavior research methods·2023
Same journal

Personal Recovery in Addictions: Development of a new Assessment Instrument.

Psicothema·2026
Same journal

Internet Habits, Problematic Internet Use, and Online Risk Practices Among Adolescents With ADHD in Spain.

Psicothema·2026
Same journal

Relationship Between Social Connectedness and Quality of Life in Older Adults: An Examination of Sex Differences.

Psicothema·2026
Same journal

The Influence of Gender on Measuring Mental Health Stigma. A Cross-Sectional Vignette Study With the Attribution Questionnaire 9.

Psicothema·2026
Same journal

Comprehensive Assessment of Mental Health Stigma.

Psicothema·2026
Same journal

Psychometric Properties of the Teachers' Responses to Bullying Questionnaire (TRBQ) in Spanish Students.

Psicothema·2026
See all related articles

This study compared two data analysis methods for ABAB designs using Monte Carlo simulations. Data-division-specific distributions offer more detailed insights into randomization test performance.

Area of Science:

  • Behavioral research methodology
  • Statistical analysis

Background:

  • ABAB designs are used to measure behavioral changes.
  • Randomization tests are suitable for analyzing ABAB data when phase changes are randomized.
  • Data analysis can utilize either data-division-specific or common distributions.

Purpose of the Study:

  • To investigate the impact of using data-division-specific versus common distributions in randomization tests for ABAB designs.
  • To understand the implications of these analytical choices on statistical power and results, particularly with zero treatment effects.

Main Methods:

  • Monte Carlo simulations were employed to generate data for ABAB designs of varying lengths.
  • Randomization tests were used as the analytical technique, with randomly determined phase change points.

Related Experiment Videos

  • Simulations considered both data-division-specific and common distribution approaches for data generation and analysis.

    • Main Results:

    • Different distribution approaches yield discrepancies in randomization test outcomes.
    • These discrepancies are particularly evident when analyzing data with no true treatment effect.
    • The choice of distribution significantly impacts the interpretation of results and statistical power.

    Conclusions:

    • Data-division-specific distributions provide a more nuanced understanding of randomization test performance in ABAB designs.
    • Awareness of these analytical differences is crucial for accurate interpretation of behavioral research findings.
    • The study highlights the importance of selecting appropriate distributional assumptions for robust statistical inference.