临床试验中统计学风险的控制(How to control statistical errors in clinical trials)_陈峰教授(Prof.Feng.Chen)
演讲嘉宾：陈峰教授，南京医科大学研究生院院长，CCTS组长
Speaker： Feng Chen, Professor of Biostatistics, Nanjing Medical University
Abstract：
New drug clinical trials, whether successful or failed, are likely to have errors. From a statistical point of view, there are two types of errors: Type I and Type II. The Type I error, also known as a false-positive error, occurs when an ineffective drug shows positive results, suggesting that the drug in question is efficacious for treating the indicated disease or condition. A Type I error is most concerning to regulatory authorities who strive to keep ineffective or harmful drugs from the market. The Type II error, also known as a false-negative error, occurs when an effective drug does not show positive results, suggesting that the drug in question is ineffective for treating the indicated disease or condition. A Type II error is most concerning to the sponsors of the trial because of the very real likelihood of keeping an effective drug from providing a return on their research investments. This report suggests statistical methods to effectively control the Type I error and minimize the Type II error in the clinical trials of new drugs.
演讲嘉宾：陈峰教授，南京医科大学研究生院院长，CCTS组长
Speaker： Feng Chen, Professor of Biostatistics, Nanjing Medical University
Abstract：
New drug clinical trials, whether successful or failed, are likely to have errors. From a statistical point of view, there are two types of errors: Type I and Type II. The Type I error, also known as a false-positive error, occurs when an ineffective drug shows positive results, suggesting that the drug in question is efficacious for treating the indicated disease or condition. A Type I error is most concerning to regulatory authorities who strive to keep ineffective or harmful drugs from the market. The Type II error, also known as a false-negative error, occurs when an effective drug does not show positive results, suggesting that the drug in question is ineffective for treating the indicated disease or condition. A Type II error is most concerning to the sponsors of the trial because of the very real likelihood of keeping an effective drug from providing a return on their research investments. This report suggests statistical methods to effectively control the Type I error and minimize the Type II error in the clinical trials of new drugs.