Answer 3 for HLT 362 Evaluate and provide examples of how hypothesis testing and confidence intervals are used together in health care research
The hypothesis is the question the researcher wants to answer, the clinical inquiry in healthcare, the research design, how the data is gathered and analyzed is determined by the question or hypothesis. In healthcare we aim to find correlations and answers within the data to provide for better patient population outcomes. Correlation does not prove causation. Clinical significance determines whether the research has a practical application to an individual or a group. It also is used to determine health care decisions made by leadership. Clinical significance is the application in improving the quality of life of an individual and provides the bridge from health research to patient care (Ambrose, 2018).
The confidence interval helps to reject the null hypothesis. The confidence interval is an interval estimate for the mean. It is a range of values that are set close to the mean either in a positive or negative direction. For the null to be rejected, 95% of the values need to be set close to the mean. The range of values determines the effect.
A CI informs the investigator and the reader about the power of the study and whether or not the data are compatible with a clinically significant treatment effect. Confidence intervals also provide a more appropriate means of analysis for studies that seek to describe or explain, rather than to make decisions about treatment efficacy. The logic of hypothesis testing uses a decision-making mode of thinking which is more suitable to randomized controlled trials (RCTs) of health care interventions. Hypothesis testing to determine statistical significance was initially intended to be used only in randomized experiments such as RCTs which are typically not feasible in clinical research involving identification of risk factors, etiology, clinical diagnosis, or prognosis. The use of CIs allows for hypothesis testing and it allows a more flexible approach to analysis that accounts for the objectives of each investigation (Savage, 2003).
Ambrose, J. (2018). Retrieved from https://lc.gcumedia.com/hlt362v/applied-statistics-for-health-care/v1.1/#/chapter/3
Savage, S. (2003). Advantages of confidence intervals in clinical research. Retrieved from: https://www.redorbit.com/news/science/18686/advantages_of_confidence_intervals_in_clinical_research/
