Simulation results when the inclusion probability in the external validation sample (notated P) depends on U1; coverage rate of 95% confidence interval (grey dot with black margin) and mean estimated log-odds ratio for the exposure effect (black dot) ± empirical standard error: (A) logit(P) = -2.2+log(2)U1, (B) logit(P) = -2.7+log(4)U1, (C) logit(P) = -2.3+log(2)U1+log(2)X*U1, (D) logit(P) = -2.5+log(2)U1+log(2)Y*U1. The grey dotted line corresponds to the nominal value of the coverage rate of the 95% confidence interval. The black dotted line is the true value of β (0).</p
Introduction. Patient-level simulation models facilitate extrapolation of clinical trial data while ...
BACKGROUND: Studies using health administrative databases (HAD) may lead to biased results since inf...
Background Observational healthcare data offer the potential to enable identification of risks of me...
Simulation results when the inclusion probability in the external validation sample (notated P) depe...
Simulation results when the inclusion probability in the external validation sample (notated P) depe...
Simulation results with a non-representative internal validation sample where the inclusion probabil...
Simulation results with a representative external validation sample (scenario 1); coverage rate of 9...
BACKGROUND:Studies using health administrative databases (HAD) may lead to biased results since info...
International audienceStudies using health administrative databases (HAD) may lead to biased results...
Health disparities are commonplace and of broad interest to policy makers, but are also challenging ...
Observational healthcare data, such as electronic health records and administrative claims, offer po...
International audienceFrench health insurance databases (SNIIRAM) cover the entire French population...
In health research, statistical methods are frequently used to address a wide variety of research qu...
Reliability is one of the most important aspects of testing in educational and psychological measure...
International audienceBACKGROUND: Participants in cohort studies are frequently selected from restri...
Introduction. Patient-level simulation models facilitate extrapolation of clinical trial data while ...
BACKGROUND: Studies using health administrative databases (HAD) may lead to biased results since inf...
Background Observational healthcare data offer the potential to enable identification of risks of me...
Simulation results when the inclusion probability in the external validation sample (notated P) depe...
Simulation results when the inclusion probability in the external validation sample (notated P) depe...
Simulation results with a non-representative internal validation sample where the inclusion probabil...
Simulation results with a representative external validation sample (scenario 1); coverage rate of 9...
BACKGROUND:Studies using health administrative databases (HAD) may lead to biased results since info...
International audienceStudies using health administrative databases (HAD) may lead to biased results...
Health disparities are commonplace and of broad interest to policy makers, but are also challenging ...
Observational healthcare data, such as electronic health records and administrative claims, offer po...
International audienceFrench health insurance databases (SNIIRAM) cover the entire French population...
In health research, statistical methods are frequently used to address a wide variety of research qu...
Reliability is one of the most important aspects of testing in educational and psychological measure...
International audienceBACKGROUND: Participants in cohort studies are frequently selected from restri...
Introduction. Patient-level simulation models facilitate extrapolation of clinical trial data while ...
BACKGROUND: Studies using health administrative databases (HAD) may lead to biased results since inf...
Background Observational healthcare data offer the potential to enable identification of risks of me...