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A PROBABILISTIC MODEL OF INTENSIVE DESIGNS
Author(s) -
Pechacek Terry F.
Publication year - 1978
Publication title -
journal of applied behavior analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 76
eISSN - 1938-3703
pISSN - 0021-8855
DOI - 10.1901/jaba.1978.11-357
Subject(s) - internal validity , probabilistic logic , external validity , criticism , psychology , research design , internal model , statistical model , computer science , econometrics , statistics , cognitive psychology , machine learning , artificial intelligence , social psychology , mathematics , art , literature , control (management)
Without internal validity, experimental data are uninterpretable. With intensive designs, most methods presented to quantify a design's internal validity have been subject to criticism. A probabilistic model of intensive designs is presented that demonstrates the high degree of internal validity of these designs without relying on adaptations from traditional inferential statistics. Where the experimenter is able to conform to the restrictions of the model, the equations provide an estimation of internal validity for either reversal or multiple‐baseline designs. More importantly, the model provides mathematical bases for some of the common recommendations and design considerations in intensive research (such as the desirability of within‐subject replications and of four or more multiple baselines).