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The sample odds ratio n 11 n 00 / n 10 n 01 is easy to calculate, and for moderate and large samples performs well as an estimator of the population odds ratio. When one or more of the cells in the contingency table can have a small value, the sample odds ratio can be biased and exhibit high variance.
Choi et al. [21] propose a p-value derived from the likelihood ratio test based on the conditional distribution of the odds ratio given the marginal success rate. This p -value is inferentially consistent with classical tests of normally distributed data as well as with likelihood ratios and support intervals based on this conditional ...
The cross-product and MLE odds ratio estimate; Mid-p exact p-values and confidence limits for the odds ratio; Calculations of rate ratios and rate differences with confidence intervals and statistical tests. For stratified 2x2 tables with count data, OpenEpi provides: Mantel-Haenszel (MH) and precision-based estimates of the risk ratio and odds ...
The log diagnostic odds ratio can also be used to study the trade-off between sensitivity and specificity [5] [6] by expressing the log diagnostic odds ratio in terms of the logit of the true positive rate (sensitivity) and false positive rate (1 − specificity), and by additionally constructing a measure, :
p-value (Wald) Intercept (β ... [21] to calculate the p-value for logistic regression is the likelihood ... The image represents an outline of what an odds ratio ...
In null-hypothesis significance testing, the p-value [note 1] is the probability of obtaining test results at least as extreme as the result actually observed, under the assumption that the null hypothesis is correct. [2] [3] A very small p-value means that such an extreme observed outcome would be very unlikely under the null hypothesis.
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Most straightforward: Predictive value equals probability: Usually low: Separate reference group required for every subsequent pre-test state: Available both for binary and continuous values: By likelihood ratio: Derived from sensitivity and specificity: Post-test odds given by multiplying pretest odds with the ratio: Theoretically limitless