เปรียบเทียบวิธี
ดูวิธีที่เลือกเทียบกันแบบเคียงข้าง แถวที่ต่างกันจะถูกเน้นไว้
| การทดลองธรรมชาติแบบปรับตัวได้× | การทดลองภาคสนาม× | |
|---|---|---|
| สาขาวิชา | การออกแบบการทดลอง | การออกแบบการทดลอง |
| ตระกูล | Process / pipeline | Process / pipeline |
| ปีกำเนิด≠ | 2000s–2010s (systematic application in policy and social science evaluation) | 1920s–1930s (agriculture); 1990s–2000s (social sciences) |
| ผู้ริเริ่ม≠ | Synthesizes natural experiment tradition (Meyer 1995; Dunning 2012) with adaptive design principles (Wald 1947; Chow & Chang 2008) | Formalized by R. A. Fisher (1935); systematized in social sciences by Harrison & List (2004) |
| ประเภท≠ | Quasi-experimental adaptive research design | Experimental design |
| แหล่งต้นตำรับ≠ | Dunning, T. (2012). Natural Experiments in the Social Sciences: A Design-Based Approach. Cambridge University Press. ISBN: 978-1107698000 | Harrison, G. W., & List, J. A. (2004). Field experiments. Journal of Economic Literature, 42(4), 1009–1055. DOI ↗ |
| ชื่อเรียกอื่น | adaptive quasi-experiment, adaptive exogenous shock design, adaptive as-if randomization, sequential natural experiment | field trial, natural field experiment, randomized field experiment, field RCT |
| ที่เกี่ยวข้อง≠ | 4 | 5 |
| สรุป≠ | An adaptive natural experiment combines the causal logic of the natural experiment — exploiting real-world events that assign individuals to conditions in a plausibly exogenous way — with pre-specified adaptive monitoring rules that allow the analytic protocol to be modified based on accumulating data. This hybrid design is used in economics, epidemiology, and policy evaluation when the natural event unfolds over time and interim evidence can legitimately inform decisions about data collection scope, subgroup focus, or analytic strategy without compromising causal validity. | 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. |
| ScholarGateชุดข้อมูล ↗ |
|
|