Table 3.
Summary of probabilistic bias analysis when simulating misclassification, sorted by study design
| Study | Type of misclassification simulated |
Source of bias parameter estimates |
Type of probability distribution assigned to bias parameters* |
Bias parameters for which assigned range of values were reported† |
Simulated iterations |
|---|---|---|---|---|---|
|
Cohort studies | |||||
| Ahrens et al. (2012)38 | Differential exposure misclassification (binary) |
Internal validation data and external validation study |
Beta | PPV and time of initiation‡ |
100,000 |
| Brunet et al. (2015)43 | Nondifferential exposure misclassification (binary) |
External validation studies |
Trapezoidal | Sensitivity and specificity |
Not reported |
| Huybrechts et al. (2014)39 | Nondifferential outcome misclassification (binary) |
Internal validation study |
Triangular | Sensitivity and specificity |
1,000 |
| Palmsten et al. (2013)40 | Nondifferential outcome misclassification (binary) |
Internal validation study |
Not reported | Not reported | Not reported |
|
Case-control studies | |||||
| Barron et al. (2013)41 | Nondifferential Outcome misclassification; differential outcome misclassification (binary) § |
External validation study; expert judgement |
Trapezoidal | Sensitivity and specificity |
5,000 |
| 5,000 | |||||
| Mahmud et al. (2011)42 | Nondifferential exposure misclassification |
Not reported | Not reported | Not reported | Not reported |
NPV, negative predictive value; PPV, positive predictive value
See eFigure 1 in the online supplementary appendix for further description of probability distribution types.
Bias parameters for misclassification include classification probabilities (sensitivity/specificity and/or PPV/NPV). We report whether investigators discussed the range of plausible values assigned to bias parameters
Simulated a time-varying exposure required estimating time-to-initiation, which investigators simulated by fitting probability distributions to the range of times observed in their cohort. Only sensitivity and specificity point estimates were provided for the calculation of NPV.
Simulated both nondifferential and differential outcome misclassification