Considering that a researcher can test at the <p = .05 (95%), p = .01 (99%), or p = .001 (99.9%) level for statistical significance, how would you use these three levels in relationship to risk to patients in implementing the decisions of your research?
It would depend on the type of research, the questions being considered, the tests involved and possible side effects of treatments considered. Can you be more specific? How sure do you want to be in rejecting Ho and avoiding alpha error?
When implementing research decisions that may impact patient outcomes, it is crucial to consider the levels of statistical significance (p-values) and the associated risk thresholds. The choice of the significance level should be based on the level of risk deemed acceptable in the context of patient well-being and the consequences of making a wrong decision.
1. p = .05 (95% significance level): This is the most commonly used significance level in research. It means that if the p-value is less than .05, there is a 5% or less probability of observing the results by chance alone. This level is suitable when the risk associated with a wrong decision is relatively low and reversible or when additional evidence can be obtained to support or refute the findings before making significant changes to patient care.
2. p = .01 (99% significance level): This level of significance is more conservative and indicates a higher threshold for accepting statistical significance. It implies that if the p-value is less than .01, there is a 1% or less probability of obtaining the results by chance alone. This level is appropriate when the risk associated with a wrong decision is relatively higher, and the consequences of making an incorrect conclusion could have significant patient impact. It may be suitable for critical decisions or interventions with potential severe consequences.
3. p = .001 (99.9% significance level): This level represents an even more conservative approach, reducing the risk of making a Type I error (false positive) to 0.1%. It suggests that if the p-value is less than .001, there is a 0.1% or less probability of obtaining the results by chance alone. This level is suitable for contexts where the risk associated with a wrong decision is extremely high, and the potential harm to patients is severe. It may be applied in situations involving life-threatening conditions or irreversible treatments.
Ultimately, the choice of the significance level should be made in consultation with experts and considering the ethics and potential consequences of the research decisions on patient well-being. It is important to strike a balance between minimizing the risk of incorrect conclusions and the need for timely and appropriate actions to improve patient care.