Statistical Methods in Medical Research

Papers
(The H4-Index of Statistical Methods in Medical Research is 19. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-08-01 to 2025-08-01.)
ArticleCitations
Exact interval estimation for the linear combination of binomial proportions153
A Bayesian beta-binomial piecewise growth mixture model for longitudinal overdispersed binomial data93
Omnibus test for restricted mean survival time based on influence function77
Interval estimation in three-class receiver operating characteristic analysis: A fairly general approach based on the empirical likelihood64
Covariate adjustment in Bayesian adaptive randomized controlled trials35
Confidence estimation based on data from independent studies34
Time-varying coefficient additive hazards model with latent variables31
Semiparametric copula method for semi-competing risks data subject to interval censoring and left truncation: Application to disability in elderly30
Equivalence tests for ratio of means in bioequivalence studies under crossover design30
Analysis of hospital readmissions with competing risks29
A new cure model accounting for longitudinal data and flexible patterns of hazard ratios over time25
Joint meta-analysis of two diagnostic tests accounting for within and between studies dependence23
Commentary on the use of the reproduction number R during the COVID-19 pandemic22
Generalized Bayesian kernel machine regression22
Generalised pairwise comparisons for trend: An extension to the win ratio and win odds for dose-response and prognostic variable analysis with arbitrary statements of outcome preference21
Accounting for informative observation process in transition models of binary longitudinal outcome: Application to medical record data20
Modeling and estimating a threshold effect: An application to improving cardiac surgery practices20
Developing clinical prediction models when adhering to minimum sample size recommendations: The importance of quantifying bootstrap variability in tuning parameters and predictive performance19
Analyzing heterogeneity in biomarker discriminative performance through partial time-dependent receiver operating characteristic curve modeling19
Response-adaptive treatment randomization for multiple comparisons of treatments with recurrent event responses19
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