Compară metode

	Experiment factorial fracțional pragmatic	Experiment factorial complet
Domeniu	Design experimental	Design experimental
Familie	Process / pipeline	Process / pipeline
Anul apariției	Fractional factorial designs: 1940s–1950s; pragmatic application: 2000s–2010s	1926 (Fisher's foundational paper); codified by the 1950s–1960s
Autorul original	Building on Fisher (1935); pragmatic adaptation by Collins, Murphy & Strecher (2007) via MOST framework	Ronald A. Fisher
Tip	Experimental design	Experimental design
Sursa seminală	Collins, L. M., Murphy, S. A., & Strecher, V. (2007). The multiphase optimization strategy (MOST) and the sequential multiple assignment randomized trial (SMART): New methods for more potent eHealth interventions. American Journal of Preventive Medicine, 32(5S), S112–S118.	Box, G. E. P., Hunter, J. S., & Hunter, W. G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed.). Wiley-Interscience. ISBN: 978-0471718130
Denumiri alternative	pragmatic FFE, fractional factorial trial, pragmatic factorial design, FFD in pragmatic settings	full factorial design, complete factorial design, 2^k factorial design, FFD
Înrudite	4	6
Rezumat	A pragmatic fractional factorial experiment applies fractional factorial design principles to real-world or clinical intervention research, enabling simultaneous evaluation of multiple intervention components in a resource-efficient fraction of the full factorial runs. Popularised through the Multiphase Optimization Strategy (MOST), it identifies which components of a multi-component intervention contribute meaningfully to outcomes before a confirmatory randomized trial is conducted.	A full factorial experiment runs every possible combination of all chosen factor levels, making it the gold standard for simultaneously estimating main effects, two-way interactions, and higher-order interactions among multiple independent variables. Introduced through Ronald Fisher's foundational work on factorial designs in the 1920s and systematised by Box, Hunter, and Montgomery, it provides complete information about how factors act individually and in combination on an outcome.