2 citations · 2 across the 5 of their papers we have counts for
5 papers
Applying the Weibull Shape Parameter test for signal detection in pharmacovigilance using the R package WSPsignal
Julia Dyck, Odile Sauzet
Post-marketing pharmacovigilance relies on statistical signal detection methods to identify potential adverse drug reactions. The Weibull shape parameter (WSP) test concept exploit…
The BPgWSP test: a Bayesian Weibull Shape Parameter signal detection test for adverse drug reactions
Julia Dyck, Odile Sauzet
We develop the Bayesian Power generalized Weibull shape parameter (BPgWSP) test as statistical method for signal detection of possible drug-adverse event associations using electro…
Optimal p-values and sample size for signal detection methods based on generalised Weibull distributions
Odile Sauzet, Julia Dyck, Victoria Cornelius
Objectives: Statistical methods for signal detection of adverse drug reactions in electronics health records (EHRs) are not usually provided with information about optimal p-values…
EgoCor: an R package to facilitate the use of exponential semi-variograms for modelling the local spatial correlation structure in social epidemiology
Julia Dyck, Jan-Ole Koslik, Odile Sauzet
As an alternative to using administrative areas for the evaluation of small-area health inequalities, Sauzet et al. suggested to take an ego-centred approach and model the spatial…
Parameter uncertainty estimation for exponential semi-variogram models: Two generalized bootstrap methods with check- and quantile-based filtering
Julia Dyck, Odile Sauzet
The estimation of parameter standard errors for semi-variogram models is challenging, given the two-step process required to fit a parametric model to spatially correlated data. Mo…