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Likelihood ratios (2xk table)

Command:Tests
Next selectLikelihood ratios (2xk table)

Description

Allows to calculate likelihood ratios for different test levels from a 2xk table.

When test results have a continuous or ordinal outcome then valuable information is lost when the data are dichotomized for the calculation of sensitivity, specificity and likelihood ratios as in ROC curve analysis.

Interval likelihood ratios may be more powerful because they use more information contained in the data.

The likelihood ratio can be used to calculate the post-test probability of disease from the pre-test probability of disease (see below).

Required input

Enter the number of cases in the diseased group that test positive and negative at the different test levels.

Dialog box for likelihood ratios (2xk table)

Results

For each test levels the program calculates corresponding Likelihood ratio with 95% Confidence interval.

Confidence intervals for the likelihood ratios are calculated using the "Log method" as given on page 109 of Altman et al. 2000.

The likelihood ratio can be used to calculate the post-test odds from the pre-test odds of disease:

Calculate the post-test odds from the pre-test odds of disease

The relation between odds and probability is:

Relation between odds and probability

Using these equations, you can calculate the post-test probability of disease from the pre-test probability of disease.

If, for example, the pre-test probability of disease is 0.6 then the pre-test odds is 0.6/(1-0.6) = 1.5. For a case with a test result corresponding with diagnostic level 2, the likelihood ratio is 12, and the post-test odds is 1.5 x 12 = 18. The post-test probability of disease is 18/(1+18) = 0.95.

In the Comment input field you can enter a comment or conclusion that will be included on the printed report.

Literature

See also

Recommended book

Book cover

Statistics with Confidence: Confidence Intervals and Statistical Guidelines
Altman DG, Machin D, Bryant TN, Gardner MJ (Eds)

Buy from Amazon

This introduction to confidence intervals has been updated and expanded to include methods for using confidence intervals, with illustrative worked examples and extensive guidelines and checklists to help the novice. There are six new chapters on areas such as diagnostic studies and meta-analyses.