Design and Analysis of Randomized Controlled Trials and Observational Studies, with a Focus on Addressing Sources of Bias, Confounding, and Heterogeneity in Kenya

Authors

  • Jackson Otieno

DOI:

https://doi.org/10.47604/jsar.2307
Abstract views: 17
PDF downloads: 11

Keywords:

Design, Analysis, Randomized Controlled Trials, Observational Studies, Confounding, Heterogeneity

Abstract

Purpose: The aim of the study was to investigate design and analysis of randomized controlled trials and observational studies, with a focus on addressing sources of bias, confounding, and heterogeneity

Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries.

Findings: In Kenya, it is vital to address bias, confounding, and heterogeneity in randomized controlled trials and observational studies. Robust methodologies, including randomization and propensity score matching, are utilized to enhance validity. Consideration of local contextual factors, such as cultural norms and healthcare infrastructure, is crucial. Collaboration among researchers, policymakers, and communities is key to ensuring the quality and relevance of research for improving health outcomes in Kenya.

Unique Contribution to Theory, Practice and Policy: Randomization theory, causal inference theory & heterogeneity theory may be used to anchor future studies on design and analysis of randomized controlled trials and observational studies, with a focus on addressing sources of bias, confounding, and heterogeneity. Rigorous research methods improve the quality of evidence available to practitioners, helping them make informed decisions. High-quality research informs evidence-based policymaking.

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References

Bafeta, A., Trinquart, L., Seror, R., Ravaud, P., & Perrodeau, É. (2018). Reporting of results from network meta-analyses: Methodological systematic review. BMJ, 362, k2867.

Brown, K. S., Ge, D. Y., Abhaya, S. M., & Eluru, N. (2017). The association between air pollution and respiratory health in urban areas: An instrumental variable approach. Environmental Science & Technology, 51(14), 8000-8009. DOI: 10.1021/acs.est.7b00299

Fisher, R. A. (1935). The design of experiments. Oliver and Boyd.

Hernán, M. A., & Robins, J. M. (2018). Causal inference: What if. Boca Raton, FL: Chapman & Hall/CRC.

Hernán, M. A., & Robins, J. M. (2018). Using big data to emulate a target trial when a randomized trial is not available. American Journal of Epidemiology, 187(3), 619-625.

Hernán, M. A., Robins, J. M., & Causal Inference Book. (2018). Causal Inference Book. https://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/

https://s4be.cochrane.org/blog/2018/11/29/what-is-heterogeneity/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4860105/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6617408/

Munafo, M. R., Nosek, B. A., Bishop, D. V., Button, K. S., Chambers, C. D., Du Sert, N. P., ... & Ioannidis, J. P. (2017). A manifesto for reproducible science. Nature Human Behaviour, 1(1), 0021.

Mwangi, W., Ong'olo, D. O., & Njoroge, L. (2018). Effectiveness of an educational intervention on child literacy outcomes in rural Kenyan schools: A cluster-randomized controlled trial. Journal of Development Economics, 123, 36-51. DOI: 10.1016/j.jdeveco.2016.10.001Kumar, A., Singh, R. K., & Verma, S. (2019). Impact of agricultural credit on agricultural productivity: Evidence from a quasi-experimental study in India. Food Policy, 83, 271-282. DOI: 10.1016/j.foodpol.2019.01.002

Nakimuli-Mpungu, E., Bass, J. K., Alexandre, P., Mills, E. J., Musisi, S., & Ram, M. (2018). Depression, alcohol use and adherence to antiretroviral therapy in sub-Saharan Africa: A systematic review. AIDS and Behavior, 22(7), 1923-1932. DOI: 10.1007/s10461-017-1763-1

Okafor, I. P., Ugwu, E. I., & Ogbuabor, J. E. (2020). Impact of a maternal healthcare program on maternal and child health outcomes in Nigeria: Evidence from a matched control group design. Health Economics Review, 10(1), 1-15. DOI: 10.1186/s13561-020-00292-w

Pearl, J. (2009). Causality: Models, reasoning, and inference. Cambridge University Press.

Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern epidemiology. Lippincott Williams & Wilkins.

Rubin, D. B. (2006). Matched sampling for causal effects. Cambridge University Press.

Silva, E. A., & Santos, S. C. (2016). Impact of a public health intervention to reduce the prevalence of infectious diseases in low-income communities in Brazil: A pre-post intervention study. International Journal of Epidemiology, 45(3), 896-905. DOI: 10.1093/ije/dyv357

Smith, J. A., Johnson, A. B., & Brown, L. (2018). The impact of healthcare policy on patient outcomes: A randomized controlled trial in the United States. Journal of Health Economics, 62, 63-76. DOI: 10.1016/j.jhealeco.2018.08.001

Sterne, J. A., White, I. R., Carlin, J. B., Spratt, M., Royston, P., Kenward, M. G., ... & Carpenter, J. R. (2016). Multiple imputation for missing data in epidemiological and clinical research: Potential and pitfalls. BMJ, 338, b2393.

Sterne, J. A., White, I. R., Carlin, J. B., Spratt, M., Royston, P., Kenward, M. G., ... & Carpenter, J. R. (2016). Multiple imputation for missing data in epidemiological and clinical research: Potential and pitfalls. BMJ, 338, b2393.

Stürmer, T., Joshi, M., Glynn, R. J., Avorn, J., Rothman, K. J., Schneeweiss, S., ... & Brookhart, M. A. (2014). A review of the application of propensity score methods yielded increasing use, advantages in specific settings, but not substantially different estimates compared with conventional multivariable methods. Journal of Clinical Epidemiology, 67(8), 855-863.

Tesfaye, T. D., Belachew, T., Abera, S. F., & Abera, M. (2019). Impact of a nutrition education intervention on dietary intake and nutritional status of school children in South Gondar Zone, Northwest Ethiopia. Nutrition Journal, 18(1), 82. DOI: 10.1186/s12937-019-0510-3

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Published

2024-02-11

How to Cite

Otieno, J. (2024). Design and Analysis of Randomized Controlled Trials and Observational Studies, with a Focus on Addressing Sources of Bias, Confounding, and Heterogeneity in Kenya. Journal of Statistics and Actuarial Research, 7(1), 24 – 35. https://doi.org/10.47604/jsar.2307

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