Porovnat metody

	Pragmatický laboratorní experiment	Úplný faktorový experimentální design
Obor	Plánování experimentů	Plánování experimentů
Rodina	Process / pipeline	Hypothesis test
Rok vzniku	1967 (foundational distinction); 2009 (PRECIS operationalization)	1926
Tvůrce	Schwartz & Lellouch (pragmatic–explanatory distinction); extended by PRECIS framework developers	R. A. Fisher
Typ	Experimental design philosophy and study type	Parametric factorial experiment
Původní zdroj	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
Další názvy	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)
Příbuzné	3	5
Shrnutí	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.