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Table 4 Summary of model performance for the developed model by apparent, split sample, bias-corrected internal validation and external validation estimates

From: Sample size requirements are not being considered in studies developing prediction models for binary outcomes: a systematic review

Model performance measure

Number of studies (%, 95% CI)

Median [p25-p75]

Range

R-squared reported

11 (9%, 95% CI: 5–16%)

Apparent*

1

0.06 [-]

-

Split sample

6

0.31 [0.15–0.34]

0.12 to 0.45

Bias corrected

5

0.35 [0.11–0.64]

0.01 to 0.89

External validation*

1

0.88 [-]

-

C-statistic reported

116 (97%, 95% CI: 92–99%)

Apparent

52

0.84 [0.76–0.91]

0.63 to 0.99

Split sample

43

0.81 [0.74–0.88]

0.61 to 1.00

Bias corrected

53

0.84 [0.75–0.90]

0.59 to 1.00

External validation

16

0.81 [0.73–0.88]

0.67 to 0.96

Calibration-in-the-large reported

10 (8%, 95% CI: 4–15%)

Apparent

10

0.01 [-0.02–0.18]

-0.26 to 1.82

Split sample*

1

-0.01 [-]

-

Bias corrected

0

-

-

External validation

0

-

-

Calibration slope reported

9 (8%, 95% CI: 4–14%)

Apparent

9

0.99 [0.98 to 1.00]

-0.22 to 1.02

Split sample*

1

1.02 [-]

-

Bias corrected

0

-

-

External validation

0

-

-

  1. *25th, 75th and range not specified as only one model performance estimate was reported