![]() ![]() Historically, factorial experiments in education have been rare, in part because of the large sample sizes required. Such an experimental design may be used to study heterogeneity in treatment effects by identifying the groups for which a treatment is most or least beneficial. In addition to reflecting differences in treatment, the factors of a factorial experiment can encode differences in treated populations (such as by age groups or gender). Table 1 shows the six treatment arms of this example (3 × 2) configuration. This design has two factors (lesson length and teaching strategy) that have three and two levels, respectively (30, 60, and 90 min lessons standard teachers and math specialists). A factorial experiment assigns classes to a random lesson length and random teaching strategy, so that all combinations of lesson length and teaching strategy are tested. Since there is the possibility of interaction effects (math specialists may be particularly effective in a longer teaching session), these two factors cannot be tested separately. For example, in a hypothetical study of new math curricula, a researcher might want to study different lesson lengths (30, 60, or 90 min per day) and different teaching strategies (whether to deliver lessons using standard classroom teachers or math specialists). A factorial experiment moves beyond basic treatment–control comparison and examines the effects of multiple implementation “factors” such as different dosages and implementation strategies, along with the interactions between these factor levels. Wolfram Language & System Documentation Center.All subjects Allied Health Cardiology & Cardiovascular Medicine Dentistry Emergency Medicine & Critical Care Endocrinology & Metabolism Environmental Science General Medicine Geriatrics Infectious Diseases Medico-legal Neurology Nursing Nutrition Obstetrics & Gynecology Oncology Orthopaedics & Sports Medicine Otolaryngology Palliative Medicine & Chronic Care Pediatrics Pharmacology & Toxicology Psychiatry & Psychology Public Health Pulmonary & Respiratory Medicine Radiology Research Methods & Evaluation Rheumatology Surgery Tropical Medicine Veterinary Medicine Cell Biology Clinical Biochemistry Environmental Science Life Sciences Neuroscience Pharmacology & Toxicology Biomedical Engineering Engineering & Computing Environmental Engineering Materials Science Anthropology & Archaeology Communication & Media Studies Criminology & Criminal Justice Cultural Studies Economics & Development Education Environmental Studies Ethnic Studies Family Studies Gender Studies Geography Gerontology & Aging Group Studies History Information Science Interpersonal Violence Language & Linguistics Law Management & Organization Studies Marketing & Hospitality Music Peace Studies & Conflict Resolution Philosophy Politics & International Relations Psychoanalysis Psychology & Counseling Public Administration Regional Studies Religion Research Methods & Evaluation Science & Society Studies Social Work & Social Policy Sociology Special Education Urban Studies & Planning BROWSE JOURNALSįactorial experiments, which have long been used in agriculture and engineering ( Cox, 1958), allow researchers to efficiently test a larger and richer set of related programs or practices in a single study. "Factorial2." Wolfram Language & System Documentation Center. Wolfram Research (1988), Factorial2, Wolfram Language function, (updated 2022). Cite this as: Wolfram Research (1988), Factorial2, Wolfram Language function, (updated 2022). ![]()
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