Statistical issues in survival analysis (HR defense)
October 7, 2026 The authors discuss in their short communication whether the hazard function should be used for causal inference in tie-to-event studies and they consider three different potential outcome frameworks (by Rubin, Robins, and Pearl) respectively as well...
Statistical issues in survival analysis (NPH hetero covs) September 23, 2026 Currently there is no unified framework for incorporating heterogeneously time-varying effects of covariates. Such effects occur when a covariate affects survival not only in a heterogeneous...
Statistical issues in general (adaptive Lasso for Cox model)
September 10, 2026 The authors proposed use of an outcome-adaptive Lasso (OAL) Cox proportional hazards model as a novel variable selection framework causal inference for right censored data in light of a critical limitation in survival analysis where...
Statistical issues in general (Being human in preclinical research)
August 26, 2026 In their article, Lang et al (2026) discuss the issues of assessing quality in preclinical research statistically in the age of the emerging use of artificial intelligence (AI). They aimed to show how large language models (LLMs) and more generally...
Statistical issues in survival analysis (deep AFT interval-censored)
August 12, 2026 The authors, Qiang et al (2026) proposed a semiparametric modeling framework for interval-censored data using a deep generalized accelerated hazards model (DGAHM) which uses Cox proportional hazard regression or accelerated failure time (AFT)...
Statistical issues in survival analysis (ML and model comparison)
July 29, 2026 The authors published this second article as a two part series about exploring novel approaches to predicting survival outcomes and evaluating model performance. They also provide R code to help in the implementations of these. They then go through and...
Statistical issues in general (Multiple testing guiding principles)
July 15, 2026 In the literature, there has been conflicting guidance about when to use multiple testing correction or adjustment. Also, the distinction between a confirmatory vs an exploratory analyses can make all the difference. The guidance has usually been that it...
Statistical issues in survival analysis (Causal effects on nonterminal event time)
July 1, 2026 The authors were motivated by comparing future antibiotic resistance levels from different treatments but found some challenges as patients may only survive under one of the treatments. They approached this through a time-to-event analysis and...
Statistical issues in general (EPI: unconfounding in observational studies)
June 17, 2026 In this paper, the authors have described a simple strategy for empirically assessing the plausibility of conditional unconfoundedness (i.e., whether the candidate adjustment set of covariates suffices for confounding adjustment), which does not require...
Statistical issues in general (Causal effects with TMLE: missing data)
June 3, 2026 The authors evaluated the performance of targeted maximum likelihood estimation (TMLE) for estimating the average treatment effect in missing data scenarios under varying levels of positivity violations. Directed acyclic graphs (DAGs) have been used in...