Contents
What should be included in a method comparison study?
Method comparison should be based on the carefully planned study. Properly designed experiment and adequate statistical procedures for data analysis are the key to valid method comparison and reliable assessment of method trueness. When performing a method comparison, below requirements must be kept in mind:
Why is the selection of a statistical method important?
Selection of appropriate statistical method is very important step in analysis of biomedical data. A wrong selection of the statistical method not only creates some serious problem during the interpretation of the findings but also affects the conclusion of the study.
Which is the best method for comparability of measurements?
Correlation analysis and t-test are not appropriate methods for analyzing the comparability of measurements. Before data analysis, paired measurements should be graphically presented using the scatter plot. Scatter plot enables that outliers are detected as well as interval of values which is not covered by the analysis.
When to use independent samples in statistical analysis?
An independent samples t-test is used when you want to compare the means of a normally distributed interval dependent variable for two independent groups. For example, using the hsb2 data file, say we wish to test whether the mean for write is the same for males and females. t-test groups = female (0 1) /variables = write.
When do you use multiple comparisons in a statistical analysis?
Multiple comparisons arise when a statistical analysis involves multiple simultaneous statistical tests, each of which has a potential to produce a “discovery.”.
How are difference plots used in method comparison studies?
Difference plots are commonly used graphical methods aimed at describing the agreement between two measurement methods in method comparison studies [4].
How many patients are used to compare two methods?
At least 40 and preferably 100 patient samples should be used to compare two methods. Larger sample size is preferable to identify unexpected errors due to interferences or sample matrix effects. Samples should be selected with great care, taking into account the following: