Suchergebnisse

AbstractThis paper presents a procedure for recovering causal coefficients from selected samples that uses random forests, a popular machine‐learning algorithm. This proposed method makes few assumptions regarding the selection equation and the distribution of the error terms. Our Monte Carlo results indicate that our method performs well, even when the selection and outcome equations contain the same variables, as long as the selection equation is nonlinear. The method can also be used when there are many variables in the selection equation. We also compare the results of our procedure with other parametric and semiparametric methods using real data.

Research studies on breast cancer awareness with a view to inform policy are few and far between in the Arab region. When we set out to conduct this study and overall project in Oman, the literature showed that in the Arab world there was a general lack of awareness of breast cancer. This lack of awareness has determinants of a social nature, but most of the research conducted has taken on a medical perspective and has not inspired or prompted health promotion schemes or policy reviews. These research studies did not use any instrument developed or even adapted for the region's populations and its idiosyncrasies. Our project dedicated a significant amount of time to researching awareness measurement instruments specific to breast cancer, studying options on developing a new measure, or adapting a readily available and expert-validated instrument being used elsewhere. We adapted, translated, and validated the Breast Cancer Awareness Measur??developed and used by Cancer Research Ui`?to measure breast cancer awareness and early detection in Arab populations. In this process, we utilized and learned about the unique characteristics of our study populatio?Omani wome?which shaped our research methods and survey instruments in an iterative process to Arabicize, conduct ta'areeb (meaning "translation") of breast cancer awareness research. We would later employ this instrument in a quantitative survey of Omani women to form a baseline understanding of their awareness regarding breast cancer and early detection. This would inform the development of a culturally tailored breast cancer awareness intervention and Oman-specific health policy recommendations.