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We calculated optimism as mean apparent AUC minus mean validated AUC.
In the current study we calculated optimism based on the three positive items (Optimism_3 items), Pessimism based on the 3 negative items (Pessimism_3 items) and a total optimism score where the negative items were reverse scored and added to positive items (Optimism_6 items).
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Factor analyses have revealed two correlating components, but it is not clear what these components actually measure nor how researchers should calculate an optimism score using the LOT-R.
The estimated optimism, calculated according to the four approaches described above, along with the apparent and optimism-corrected MSE's are presented in Table 2.
Because the AUC value of our prediction model for new samples from the same population is expected to be below the calculated apparent AUC (especially because of the previous model selection incorporated in the LASSO approach), we applied bootstrap resampling as described in Steyerberg [39] to calculate an optimism-corrected AUC-value.
We used bootstrap methods, with 100 bootstrap samples, to calculate an optimism-corrected estimate of each measure of predictive accuracy (Efron and Tibshirani, 1993; Steyerberg, 2009).
The optimism score was calculated by adding the three optimism questions and the pessimism score was calculated by adding the three pessimism questions The overall LOT-R score (range: 6 30) was calculated by reverse scoring the three pessimism scores, and summing responses to all six questions.
From these models, process costs have been calculated and provide some optimism as to the commercial likelihood of the technology.
Optimism is calculated as the difference between the classification indexes obtained with the bootstrap sample and with the test sample.
We calculated the degree of optimism by repeatedly drawing a large number of different bootstrapped samples from the training data set.
Their suggestion was to treat the scale as uni-dimensional and to calculate a total optimism score from LOT-R.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com