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Table 4 Validity measures of the predictive rule

From: Prediction of poor outcomes six months following total knee arthroplasty in patients awaiting surgery

Measure Estimates in training sample Estimates with 1,000 bootstrap resamples
Sensitivity% (95% CI) 82.1 (64.4-92.1) 82.1 (66.7-95.8*)
Specificity% (95% CI) 71.7 (62.8-79.2) 71.7 (62.8-79.8*)
Positive predictive value% (95% CI) 41.8 (29.7-55.0) 41.8 (29.1-55.8*)
Negative predictive value% (95% CI) 94.2 (87.1-97.5) 94.2 (88.8-98.8*)
Positive likelihood ratio (95% CI) 2.90 (2.06-4.08) 2.90 (1.81-4.74*)
Negative likelihood ratio (95% CI) 0.25 (0.11-0.57) 0.25 (0.11-0.58*)
Area under ROC curve (95% CI) 0.77 (0.69-0.85) 0.77 (0.69-0.85*)
  1. • *95% asymptotic confidence intervals.
  2. Sensitivity: number of participants classified at risk both by the PR and the post-operative WOMAC score divided by all participants classified at risk by the post-operative WOMAC score (actual outcome).
  3. Specificity: number of participants classified not at risk by the PR and the post-operative WOMAC score divided by all participants classified not at risk by the post-operative WOMAC score (actual outcome).
  4. Positive predictive value: number of participants classified at risk by the PR and the post-operative WOMAC score divided by all participants classified at risk by the PR (predicted outcome).
  5. Negative predictive value: number of participants classified not at risk by the PR and the post-operative WOMAC score divided by all participants classified not at risk by the PR (predicted outcome).
  6. Positive likelihood ratio: sensitivity/(1-specificity).
  7. Negative likelihood ratio: (1-sensitivity)/specificity.
  8. Area under the ROC curve is defined as the area under the sensitivity vs. 1-specificity curve.