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Even allowing for the propensity of dinosaurs to get very big, this is something of an ecological anomaly.
Another strategy to adjust for the propensity score is weighting.
Thirteen covariates were chosen for the propensity score equation.
There are two different sets of strategies to adjust for the propensity score.
Estimation results of the probit model for the propensity score are shown in Appendix: Table 9.
However, neutropenic status was included in the baseline covariates for the propensity score construction.
The C-statistic indicated a goodness-of-fit of 0.95 for the propensity score model.
For the propensity score-matched cohort, 248 patients could be analyzed (Additional file 1: Appendix 4: Table S3).
It is, therefore, important to check the balance between the samples after adjusting for the propensity score.
Rosenbaum and Rubin's (1983) key insight is that adjusting for the propensity score removes bias from all observed confounding variables.
In addition, we conducted instrumental variable analysis as a confirmatory analysis for the propensity score analyses [34].
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