Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Teste A/B Duplo-Cego× | Experimento Fatorial× | |
|---|---|---|
| Área | Delineamento experimental | Delineamento experimental |
| Família | Process / pipeline | Process / pipeline |
| Ano de origem≠ | 1935 (Fisher's formal randomized design); double-blinding in A/B testing: 1990s–2000s | 1926–1935 |
| Autor original≠ | Evolved from clinical trial methodology; early systematic blinding attributed to James Lind (1753) and formalized by R. A. Fisher (1935) | Ronald A. Fisher |
| Tipo≠ | Randomized controlled experiment with blinding | Quantitative experimental design |
| Fonte seminal≠ | Schulz, K. F., Altman, D. G., & Moher, D. (2010). CONSORT 2010 Statement: Updated guidelines for reporting parallel group randomised trials. BMJ, 340, c332. DOI ↗ | Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd. link ↗ |
| Outros nomes | double-blind split test, double-blinded A/B experiment, blinded two-arm randomized experiment, double-blind controlled A/B trial | factorial design, factorial ANOVA design, multi-factor experiment, crossed-factor design |
| Relacionados≠ | 5 | 6 |
| Resumo≠ | A double-blind A/B test is a randomized experiment that compares two variants — a control (A) and a treatment (B) — while concealing group assignment from both participants and those administering or assessing the experiment. Combining the causal isolation of randomized assignment with blinding on both sides eliminates expectation-driven bias from participants and evaluator bias from analysts or administrators, producing cleaner causal estimates of treatment effect. | A factorial experiment is an experimental design in which two or more independent variables (factors) are manipulated simultaneously, and every combination of their levels is tested. Introduced by Ronald Fisher in the 1920s–1930s, it is the standard approach whenever a researcher needs to detect not only the main effect of each factor but also whether the effect of one factor depends on the level of another — the interaction effect. |
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