Search results
Results From The WOW.Com Content Network
There are two important aspects of a Gage R&R: Repeatability: The variation in measurements taken by a single person or instrument on the same or replicate item and under the same conditions. [1] Reproducibility: the variation induced when different operators, instruments, or laboratories measure the same or replicated specimen. [1]
Reproducibility, closely related to replicability and repeatability, is a major principle underpinning the scientific method.For the findings of a study to be reproducible means that results obtained by an experiment or an observational study or in a statistical analysis of a data set should be achieved again with a high degree of reliability when the study is replicated.
The repeatability coefficient is a precision measure which represents the value below which the absolute difference between two repeated test results may be expected to lie with a probability of 95%. [citation needed] The standard deviation under repeatability conditions is part of precision and accuracy. [citation needed]
Replication in statistics evaluates the consistency of experiment results across different trials to ensure external validity, while repetition measures precision and internal consistency within the same or similar experiments. [5] Replicates Example: Testing a new drug's effect on blood pressure in separate groups on different days.
The precision of a measurement system, related to reproducibility and repeatability, is the degree to which repeated measurements under unchanged conditions show the same results. [3] [4] Although the two words precision and accuracy can be synonymous in colloquial use, they are deliberately contrasted in the context of the scientific method.
There are different reasons for performing a round-robin test: determination the reproducibility of a test method or process; verification of a new method of analysis. If a new method of analysis has been developed, a round-robin test involving proven methods would verify whether the new method produces results that agree with the established method.
The coefficient of variation should be computed only for data measured on scales that have a meaningful zero (ratio scale) and hence allow relative comparison of two measurements (i.e., division of one measurement by the other). The coefficient of variation may not have any meaning for data on an interval scale. [2]
The concordance correlation coefficient is nearly identical to some of the measures called intra-class correlations.Comparisons of the concordance correlation coefficient with an "ordinary" intraclass correlation on different data sets found only small differences between the two correlations, in one case on the third decimal. [2]