How can I test for differences among curves fit to three?
But if you are doing many comparisons, you should correct for the multiple comparisons. Divide 0.05 (or whatever overall value you want) by the number of pairs of analyses you are comparing, to come up with a new stricter cut off for declaring a P value to be small enough that you can call the comparison “significant”.
How to determine the difference between two groups?
1 T-Test. A t-test is used to determine if the scores of two groups differ on a single variable. 2 Matched Pairs T-Test. 3 Analysis of Variance (ANOVA) The ANOVA (analysis of variance) is a statistical test which makes a single, overall decision as to whether a significant difference is present among three or
How is a t test used to analyze differences between groups?
The following statistical tests are commonly used to analyze differences between groups: A t-test is used to determine if the scores of two groups differ on a single variable. A t-test is designed to test for the differences in mean scores.
Is there a cutoff for statistical significance?
With statistical significance (extra sum-of-squares F test) approach, there is a traditional (albeit totally arbitrary) cutoff at P=0.05. But if you are doing many comparisons, you should correct for the multiple comparisons.
How to compare two ROC curves in Excel?
Compare 2 or more independent ROC curves. Compare 2 or more paired/correlated ROC curves. The analysis task pane opens. In the True state drop-down list, select the true condition variable. In the Positive event drop-down list, select the state that indicates the presence of the condition/event of interest.
How is the curve for a false positive calculated?
The curve is constructed by varying the cutpoint used to determine which values of the observed variable will be considered abnormal and then plotting the resulting sensitivities against the corresponding false positive rates.
How to analyze areas under a ROC curve?
This paper presents a nonparametric approach to the analysis of areas under correlated ROC curves, by using the theory on generalized U-statistics to generate an estimated covariance matrix. Research Support, U.S. Gov’t, Non-P.H.S.