Bandingkan kaedah

	Reka Bentuk Empat Kumpulan Solomon Rintis	Reka Bentuk Eksperimen Faktorial Penuh
Bidang	Reka Bentuk Eksperimen	Reka Bentuk Eksperimen
Keluarga	Process / pipeline	Hypothesis test
Tahun asal	1949 (Solomon design); pilot usage documented in experimental methodology literature from 1960s onward	1926
Pengasas	Richard L. Solomon (base design); pilot application is a standard methodological practice	R. A. Fisher
Jenis	Experimental design — pilot phase	Parametric factorial experiment
Sumber perintis	Solomon, R. L. (1949). An extension of control group design. Psychological Bulletin, 46(2), 137–150.	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	Pilot S4GD, Solomon four-group pilot study, pilot four-group pretest-posttest control design, pilot SFGD	factorial experiment, 2^k factorial, full factorial, Faktöriyel Deneme Deseni (Full Factorial, 2^k)
Berkaitan	3	5
Ringkasan	The Pilot Solomon Four-Group Design is a small-scale, preliminary implementation of the Solomon four-group experimental design. Its purpose is to test the feasibility and logistics of the full design before committing to a resource-intensive main study. The Solomon four-group design, introduced by Richard L. Solomon in 1949, controls for pretest sensitisation by using four groups — two that receive a pretest and two that do not — crossed with treatment and control conditions. Piloting this design allows researchers to estimate effect sizes, detect procedural problems, and verify that the pretest does not unduly influence posttest scores.	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.