Table 1.
Variables assessed in the re-abstraction.
Table 2.
Kappa example 1.
Table 3.
Kappa example 2.
Table 4.
Example for the Prevalence-Adjusted Bias-Adjusted Kappa (PABAK).
Fig 1.
Flow chart of sample selection for reliability assessment.
Fig 1 shows the flow chart of our study population starting from those eligible to those included in the analysis.
Fig 2.
Kappa values and their interpretation for intra-rater and inter-rater reliability.
Fig 2 shows the values of kappa for intra-rater (dark blue) and for inter-rater (light blue) reliability with their confidence intervals T for each variable under investigation.
Fig 3.
Kappa values and Prevalence-adjusted Bias-adjusted kappa values for intra-rater (a) and inter-rater reliability (b).
Fig 3a and 3b show the values of kappa compared to the the values obtained by calculating the Prevalence-adjusted Bias-adjusted kappa for intra-rater reliability (a) and inter-rater reliability (b).
Table 5.
Intra-rater reliability.
Fig 4.
Learning effect of the two raters at two points in time compared with the abstraction of the project manager.
Fig 4a and 4b show the comparison of the abstraction at two points in time of rater 1 (a) and rater 2 (b) compared to the chosen golden standard (abstraction of the project manager).
Table 6.
Inter-rater reliability.