30 citations · 43 across the 10 of their papers we have counts for
13 papers
A Guide to Estimating Conditional Average Treatment Effects in Competing Risks Settings
Daniel Klippert, Sarah Friedrich, Markus Pauly
Conditional average treatment effects (CATEs) are central to treatment decision-making in personalized medicine. In competing risks settings, estimating CATEs from survival data al…
Asymptotic properties of resampling-based processes for the average treatment effect in observational studies with competing risks
Jasmin Rühl, Sarah Friedrich
In observational studies with time-to-event outcomes, the g-formula can be used to estimate a treatment effect in the presence of confounding factors. However, the asymptotic distr…
Resampling-based confidence intervals and bands for the average treatment effect in observational studies with competing risks
Jasmin Rühl, Sarah Friedrich
The g-formula can be used to estimate the treatment effect while accounting for confounding bias in observational studies. With regard to time-to-event endpoints, possibly subject…
On the role of benchmarking data sets and simulations in method comparison studies
Sarah Friedrich, Tim Friede
Method comparisons are essential to provide recommendations and guidance for applied researchers, who often have to choose from a plethora of available approaches. While many compa…
On the role of data, statistics and decisions in a pandemic
Beate Jahn, Sarah Friedrich, Joachim Behnke +9
A pandemic poses particular challenges to decision-making because of the need to continuously adapt decisions to rapidly changing evidence and available data. For example, which co…
Is there a role for statistics in artificial intelligence?
Sarah Friedrich, Gerd Antes, Sigrid Behr +11
The research on and application of artificial intelligence (AI) has triggered a comprehensive scientific, economic, social and political discussion. Here we argue that statistics,…
Causal inference methods for small non-randomized studies: Methods and an application in COVID-19
Sarah Friedrich, Tim Friede
The usual development cycles are too slow for the development of vaccines, diagnostics and treatments in pandemics such as the ongoing SARS-CoV-2 pandemic. Given the pressure in su…
More powerful logrank permutation tests for two-sample survival data
Marc Ditzhaus, Sarah Friedrich
Weighted logrank tests are a popular tool for analyzing right censored survival data from two independent samples. Each of these tests is optimal against a certain hazard alternati…
Analysis of Multivariate Data and Repeated Measures Designs with the R Package MANOVA.RM
Sarah Friedrich, Frank Konietschke, Markus Pauly
The numerical availability of statistical inference methods for a modern and robust analysis of longitudinal- and multivariate data in factorial experiments is an essential element…
Nonparametric MANOVA in Mann-Whitney effects
Dennis Dobler, Sarah Friedrich, Markus Pauly
Multivariate analysis of variance (MANOVA) is a powerful and versatile method to infer and quantify main and interaction effects in metric multivariate multi-factor data. It is, ho…
MATS: Inference for potentially Singular and Heteroscedastic MANOVA
Sarah Friedrich, Markus Pauly
In many experiments in the life sciences, several endpoints are recorded per subject. The analysis of such multivariate data is usually based on MANOVA models assuming multivariate…
Using EEG, SPECT, and Multivariate Resampling Methods to Differentiate Between Alzheimer's and other Cognitive Impairments
Arne Bathke, Sarah Friedrich, Frank Konietschke +4
The incidence of Alzheimer's disease (AD) and other forms of dementia is increasing in most western countries. For a precise and early diagnosis, several examination modalities exi…
Permuting longitudinal data despite all the dependencies
Sarah Friedrich, Edgar Brunner, Markus Pauly
For general repeated measures designs the Wald-type statistic (WTS) is an asymptotically valid procedure allowing for unequal covariance matrices and possibly non-normal multivaria…