Drug clinical trials are analyzed using hypothesis testing methods. As we’ve
discussed, the null hypothesis in the effective stage of such trials is that the drug
being tested is ineffective. The alternative, of course, is that the drug is effective.
Explain why such tests are usually done with low α-levels.
Hypothesis testing is a statistical method used to make decisions about a population based on a sample of data. In the context of drug clinical trials, the purpose of hypothesis testing is to determine whether a drug is effective or not.
The null hypothesis (H0) in this case states that the drug being tested is ineffective, while the alternative hypothesis (Ha) suggests that the drug is effective. The goal is to gather evidence from the data in order to either reject or fail to reject the null hypothesis.
In hypothesis testing, we set a significance level, denoted as α (alpha), which represents the probability of making a Type I error, that is, rejecting the null hypothesis when it is actually true. The α-level is typically set to a low value, such as 0.05 (5%), 0.01 (1%), or even lower.
There are a few reasons why drug clinical trials are usually conducted with low α-levels:
1. Importance of patient safety: In drug trials, the primary concern is patient safety. Setting a low α-level helps minimize the risk of approving a drug that is actually ineffective, potentially leading to harmful consequences for patients.
2. Stringent evidence requirement: The medical and scientific community generally expects a high level of evidence to accept that a drug is effective. By setting a low α-level, researchers aim to ensure that the evidence supporting the effectiveness of a drug is robust and reliable.
3. Controlling for false positives: A low α-level helps control the probability of making Type I errors, or false positives, which occur when we mistakenly reject the null hypothesis. By setting a low α-level, researchers reduce the likelihood of falsely concluding that a drug is effective when it is not.
4. Statistical significance threshold: The α-level serves as the threshold for determining statistical significance. If the p-value (a measure of evidence against the null hypothesis) falls below the α-level, the results are considered statistically significant, indicating that the drug is likely effective.
By using low α-levels, drug trials aim to maintain the integrity and reliability of the results, ensuring that drugs are thoroughly evaluated before being approved for widespread use. It reduces the chances of false conclusions and helps maintain a high standard of evidence in the field of pharmacology.