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Post test probability was next estimated.
TTEST— t test (probability of statistical significance).
The test probability of P < 0.05 was assumed to be significant while the test probability of P < 0.0001 was highly significant.
ILD test probability values for the four data partitions generated using 1000 replicates.
To generate the practical application of these LRs the post test probability of having the disease will be generated using Bayes' theorem and the following formula: post test probability = likelihood ratio × pre-test probability/[1-pre-test probability × (1-likelihood ratio)].
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First, clinical decision rules are less useful to identity patients with a low pre-test probability.
This was the predicted probability of ominous outcome prior to measuring S100B (pre-test probability).
However, post-test probability depends on pre-test probability.
The post-test probability depends on the pre-test probability.
Note that pre-test probability and prevalence are used interchangeably.
First, we obtained a pre-test probability estimate.
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