Mark Bailey, Senior Analytics Software Tester, JMP Statistical Discovery LLC
Jianfeng Ding, Senior Research Statistician Developer, JMP
It is common to need to compare two populations with only a sample of each population. Statistical inference is often used to help the comparison. Our presentation is limited to statistical inference that involves two hypotheses: the null hypothesis and the alternative hypothesis. Sometimes the goal of the comparison is to provide sufficient evidence to decide that there is a significant difference between two populations. At other times, the goal is to provide sufficient evidence that there is significant equivalence, non-inferiority, or superiority between two populations. Both situations can be assisted with a hypothesis test, but they require different tests. We review these situations, the appropriate hypotheses, and the appropriate tests using common examples.
Another common comparison is between two measurements of the same quantity. This situation is broadly covered by Measurement System Analysis. Our presentation focuses instead on the Method Comparison protocol for chemical and biological assays used by pharmaceutical and biotechnology development and manufacturing. We present two methods that are available in JMP 17 to assess the accuracy of a new test method against an established reference method. One method is known as Deming regression or Fit Orthogonal in JMP. The second method is known as Passing-Bablok regression. We review the background of assessing accuracy, the unique nature of data from method comparisons, and demonstrate both regression methods with examples.
