The majority of recent empirical papers in operations management (OM) employ observational data to investigate the causal effects of a treatment, such as program or policy adoption. However, as ...
In the article that accompanies this editorial, Lu et al 5 conducted a systematic review on the use of instrumental variable (IV) methods in oncology comparative effectiveness research. The main ...
Repeated measurements of the same countries, people, or groups over time are vital to many fields of political science. These measurements, sometimes called time-series cross-sectional (TSCS) data, ...
This paper describes threats to making valid causal inferences about pandemic impacts on student learning based on cross-year comparisons of average test scores. The paper uses Spring 2021 test score ...
Decades of research have established a significant link between physical activity and health, influencing agenda setting, policy making and community awareness.1–4 However, the field continues to ...
We know that correlation does not imply causation, but careful analyses of correlations are often our only way to quantify cause and effect in domains ranging from healthcare to education. This ...
This course is available on the MSc in Applied Social Data Science, MSc in Behavioural Science, MSc in Human Geography and Urban Studies (Research), MSc in Innovation Policy, MSc in International ...
Gary Seidman profiles Stanford economist Guido Imbens, who is reshaping how researchers establish cause and effect in the real world So Imbens and his colleagues designed and tested sharper tools to ...
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