Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Experimento de Campo× | Delineamento Experimental Fatorial Completo× | |
|---|---|---|
| Área | Delineamento experimental | Delineamento experimental |
| Família≠ | Process / pipeline | Hypothesis test |
| Ano de origem≠ | 1920s–1930s (agriculture); 1990s–2000s (social sciences) | 1926 |
| Autor original≠ | Formalized by R. A. Fisher (1935); systematized in social sciences by Harrison & List (2004) | R. A. Fisher |
| Tipo≠ | Experimental design | Parametric factorial experiment |
| Fonte seminal≠ | Harrison, G. W., & List, J. A. (2004). Field experiments. Journal of Economic Literature, 42(4), 1009–1055. DOI ↗ | Box, G. E. P., Hunter, J. S., & Hunter, W. G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed.). Wiley. ISBN: 978-0471718130 |
| Outros nomes | field trial, natural field experiment, randomized field experiment, field RCT | factorial experiment, 2^k factorial, full factorial, Faktöriyel Deneme Deseni (Full Factorial, 2^k) |
| Relacionados | 5 | 5 |
| Resumo≠ | A field experiment applies the logic of a randomized controlled trial in a naturally occurring, real-world environment rather than an artificial laboratory. Participants are randomly assigned to treatment and control conditions while going about everyday activities, allowing researchers to estimate causal effects with high internal validity while preserving a level of ecological realism that laboratory settings cannot offer. The design is especially prominent in economics, public health, political science, and development research. | 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. |
| ScholarGateConjunto de dados ↗ |
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