Sammenlign metoder

	Pragmatisk laboratorieeksperiment – Praksisorientert eksperimentell design	Full Factorial Experimental Design
Fagfelt	Forsøksdesign	Forsøksdesign
Familie	Process / pipeline	Hypothesis test
Opprinnelsesår	1967 (foundational distinction); 2009 (PRECIS operationalization)	1926
Opphavsperson	Schwartz & Lellouch (pragmatic–explanatory distinction); extended by PRECIS framework developers	R. A. Fisher
Type	Experimental design philosophy and study type	Parametric factorial experiment
Opprinnelig kilde	Schwartz, D., & Lellouch, J. (1967). Explanatory and pragmatic attitudes in therapeutical trials. Journal of Chronic Diseases, 20(8), 637–648.	Box, G. E. P., Hunter, J. S., & Hunter, W. G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed.). Wiley. ISBN: 978-0471718130
Alias	pragmatic experiment, applied laboratory trial, practice-oriented lab experiment, pragmatic controlled experiment	factorial experiment, 2^k factorial, full factorial, Faktöriyel Deneme Deseni (Full Factorial, 2^k)
Relaterte	3	5
Sammendrag	A pragmatic laboratory experiment is a controlled study conducted in a laboratory setting that prioritises external validity and real-world applicability over the stringent internal controls characteristic of purely explanatory experiments. Drawing on the pragmatic–explanatory continuum formalised by Schwartz and Lellouch (1967) and later operationalised in the PRECIS framework, it asks whether an intervention works under conditions that approximate actual practice rather than ideal circumstances, making findings directly actionable for decision-makers and practitioners.	A full factorial design is a parametric experimental method in which every combination of factor levels is tested simultaneously, enabling the estimation of all main effects and all interaction effects in a single study. Rooted in R. A. Fisher's foundational work on designed experiments (1926) and systematically developed by Box, Hunter, and Hunter (2005) and Montgomery (2017), the 2^k form tests k two-level factors across 2^k experimental runs and is the benchmark against which all other factorial designs are measured.