The journal article entitled Estimating Causal Effects from Epidemiological Data assesses a specific condition that can permit the estimation of causal effects using observational data. Hernan and Robins (2006) used two methods in their study to estimate the causal effect: the methods of standardisation and probability weighting. The study shows the similarities in the results through the use of the two analytical approaches under the same assumptions and exposure or risk levels.
This study by Hernan and Robins cannot conclude that the measure of association is generally the causation because the exposed and unexposed population are not exchangeable. In addition to that, the two methods that they used yielded the result for the entire population which means that it holds true also for every subset of that given population. Maldonado and Greenland (2002) also said that causal effect is effective in studying one target population under two varying exposure levels.
The researchers of the study used observational data in conducting the research. Mann (2003) stated that observational research is very helpful especially in clinical studies to determine the cause, incidence, prevalence of diseases as well as the effect of treatments. Observational research method uses observation which is one of the basic forms in solving an inquiry (Advantages of Observational Methods, n.d.). Observational study can have strong and valid results but can be too subjective and might take a long of time to conduct. It can be also be useful when people are not available to answer questionnaires or for interview (Advantages of Observational Research, n.d.). We just need to know the proper approach in conducting our studies and researches to be successful in achieving the best results.
References
Advantages of Observational Methods. (n.d.). Retrieved from Preserve Articles: Advantages of Observational Methods
Advantages of Observational Research. (2012). Retrieved from Primary Data Collection- Observation: compass.port.ac.uk/UoP/file/664e8001-f121-4e5d-aa06-6c95c797e8af/1/Observations_IMSLRN.zip/page_04.htm
Hernan M. and Robins J. (2006). Estimating causal effects from epidemiological data. Journal of Epidomology and Community Health, 578-586.
Maldonaldo G. and Greenland S. (2002). Estimating causal effect. International Journal of Epidemiology, 422-429.
Mann, C. (2003). Observational research methods. Research design II: cohort, cross sectional, and case-control studies. Emergency Medicine Journal , 54-60.
