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Table 3 Scenario (I): performance of the estimated propensity score (PS) model by simulation setting assuming n = 200

From: Treatment effect estimation using the propensity score in clinical trials with historical control

Performance measurement

PS model

Outcome event rate

Odds ratio

1.0

2.0

5.0

10.0

Bias

\(\pi\) (without \(X_\textit{r}\))

50%

-0.001

0.002

0.034

0.112

10%

-0.199

-0.076

-0.007

0.104

5%

-1.264

-0.356

0.312

1.424

\({\pi }^{*}\) (with \(X_\textit{r}\))

50%

0.030

0.029

0.048

0.105

10%

-0.101

0.006

0.069

0.187

5%

-1.087

-0.218

0.447

1.593

MSE

\(\pi\)

50%

0.229

0.245

0.336

0.865

10%

1.835

0.555

0.611

1.618

5%

22.016

7.358

7.516

25.242

\({\pi }^{*}\)

50%

0.187

0.202

0.271

0.711

10%

1.636

0.493

0.605

1.702

5%

20.447

6.941

8.031

27.171

Coverage (%)

\(\pi\)

50%

93.3

93.2

92.5

90.6

10%

91.8

92.5

93.2

93.9

5%

88.4

91.2

92.1

85.8

\({\pi }^{*}\)

50%

94.2

94.4

93.8

93.4

10%

93.6

93.2

93.2

93.6

5%

89.3

92.8

92.9

87.2

Type I error and power (%)

\(\pi\)

50%

6.5

35.7

88.0

96.7

10%

8.1

21.5

74.9

94.7

5%

11.4

16.7

51.9

78.2

\({\pi }^{*}\)

50%

5.6

41.2

92.8

98.1

10%

6.1

26.4

79.3

95.5

5%

10.6

21.0

60.3

83.1

  1. \(\pi\) (without \(X_\textit{r}\)): the conventional method; \({\pi }^{*}\) (with \(X_\textit{r}\)): the proposed method