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| Reka Bentuk Eksperimen Kumpulan Kawalan Buta Tunggal× | Reka Bentuk Eksperimen Kumpulan Kawalan× | |
|---|---|---|
| Bidang | Reka Bentuk Eksperimen | Reka Bentuk Eksperimen |
| Keluarga | Process / pipeline | Process / pipeline |
| Tahun asal≠ | Mid-20th century (blinding standards consolidated ~1950s–1970s) | 1935 (Fisher); 1963 (Campbell & Stanley codification) |
| Pengasas≠ | Classical experimental tradition; blinding formalized in 20th-century clinical trial methodology | Ronald A. Fisher; systematised by Donald T. Campbell & Julian C. Stanley |
| Jenis≠ | Controlled experimental design | Experimental research design |
| Sumber perintis≠ | Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Houghton Mifflin. ISBN: 978-0395615560 | Campbell, D. T., & Stanley, J. C. (1963). Experimental and Quasi-Experimental Designs for Research. Rand McNally. link ↗ |
| Alias | single-masked controlled experiment, single-blind controlled trial, SB-CGD, single-blind parallel-group design | controlled experiment, true experimental design, randomized controlled design, treatment-control design |
| Berkaitan≠ | 6 | 4 |
| Ringkasan≠ | A single-blind control group experimental design is a controlled experiment in which participants are kept unaware of whether they are receiving the active treatment or a control condition, while researchers and outcome assessors remain unmasked. The design uses a designated control group as the baseline for comparison, allowing causal inference about the treatment effect while limiting participant-driven response biases such as the placebo effect and demand characteristics. | Control group experimental design is a fundamental experimental structure in which participants are assigned to at least two groups — a treatment group that receives the intervention and a control group that does not — so that the effect of the intervention can be isolated by comparing outcomes across groups. Randomisation of assignment strengthens causal inference by balancing known and unknown confounders. |
| ScholarGateSet data ↗ |
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