Works matching IS 0006341X AND DT 2023 AND VI 79 AND IP 3
Results: 94
Model uncertainty quantification in Cox regression.
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- Biometrics, 2023, v. 79, n. 3, p. 1726, doi. 10.1111/biom.13823
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Probability and random variables: theory and applications.
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- Biometrics, 2023, v. 79, n. 3, p. 2770, doi. 10.1111/biom.13875
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Generalized propensity score approach to causal inference with spatial interference.
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- Biometrics, 2023, v. 79, n. 3, p. 2220, doi. 10.1111/biom.13745
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Marginal proportional hazards models for clustered interval‐censored data with time‐dependent covariates.
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- Biometrics, 2023, v. 79, n. 3, p. 1670, doi. 10.1111/biom.13787
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Mendelian randomization: methods for causal inference using genetic variants 2nd edition.
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- Biometrics, 2023, v. 79, n. 3, p. 2771, doi. 10.1111/biom.13874
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Fundamentals of high‐dimensional statistics: with exercises and R Labs.
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- Biometrics, 2023, v. 79, n. 3, p. 2772, doi. 10.1111/biom.13884
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Age‐related model for estimating the symptomatic and asymptomatic transmissibility of COVID‐19 patients.
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- Biometrics, 2023, v. 79, n. 3, p. 2525, doi. 10.1111/biom.13814
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Non‐parametric estimation of the age‐at‐onset distribution from a cross‐sectional sample.
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- Biometrics, 2023, v. 79, n. 3, p. 1701, doi. 10.1111/biom.13804
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Adjusting for publication bias in meta‐analysis via inverse probability weighting using clinical trial registries.
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- Biometrics, 2023, v. 79, n. 3, p. 2089, doi. 10.1111/biom.13822
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Fast Bayesian inference for large occupancy datasets.
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- Biometrics, 2023, v. 79, n. 3, p. 2503, doi. 10.1111/biom.13816
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Consistent estimation of the number of communities via regularized network embedding.
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- Biometrics, 2023, v. 79, n. 3, p. 2404, doi. 10.1111/biom.13815
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Bayesian regression analysis of skewed tensor responses.
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- Biometrics, 2023, v. 79, n. 3, p. 1814, doi. 10.1111/biom.13743
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Estimating tree‐based dynamic treatment regimes using observational data with restricted treatment sequences.
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- Biometrics, 2023, v. 79, n. 3, p. 2260, doi. 10.1111/biom.13754
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Bayesian sample size calculations for comparing two strategies in SMART studies.
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- Biometrics, 2023, v. 79, n. 3, p. 2489, doi. 10.1111/biom.13813
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Inference for the dimension of a regression relationship using pseudo‐covariates.
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- Biometrics, 2023, v. 79, n. 3, p. 2394, doi. 10.1111/biom.13812
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Two‐level Bayesian interaction analysis for survival data incorporating pathway information.
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- Biometrics, 2023, v. 79, n. 3, p. 1761, doi. 10.1111/biom.13811
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Correcting delayed reporting of COVID‐19 using the generalized‐Dirichlet‐multinomial method.
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- Biometrics, 2023, v. 79, n. 3, p. 2537, doi. 10.1111/biom.13810
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Tensor response quantile regression with neuroimaging data.
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- Biometrics, 2023, v. 79, n. 3, p. 1947, doi. 10.1111/biom.13809
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Efficient and robust approaches for analysis of sequential multiple assignment randomized trials: Illustration using the ADAPT‐R trial.
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- Biometrics, 2023, v. 79, n. 3, p. 2577, doi. 10.1111/biom.13808
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An information ratio‐based goodness‐of‐fit test for copula models on censored data.
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- Biometrics, 2023, v. 79, n. 3, p. 1713, doi. 10.1111/biom.13807
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Design considerations for two‐stage enrichment clinical trials.
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- Biometrics, 2023, v. 79, n. 3, p. 2565, doi. 10.1111/biom.13805
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A general modeling framework for open wildlife populations based on the Polya tree prior.
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- Biometrics, 2023, v. 79, n. 3, p. 2171, doi. 10.1111/biom.13756
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Assessing exposure‐time treatment effect heterogeneity in stepped‐wedge cluster randomized trials.
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- Biometrics, 2023, v. 79, n. 3, p. 2551, doi. 10.1111/biom.13803
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Nonparametric scanning tests of homogeneity for hierarchical models with continuous covariates.
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- Biometrics, 2023, v. 79, n. 3, p. 2063, doi. 10.1111/biom.13801
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Efficient targeted learning of heterogeneous treatment effects for multiple subgroups.
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- Biometrics, 2023, v. 79, n. 3, p. 1934, doi. 10.1111/biom.13800
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Identifying alert concentrations using a model‐based bootstrap approach.
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- Biometrics, 2023, v. 79, n. 3, p. 2076, doi. 10.1111/biom.13799
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Hospital profiling using Bayesian decision theory.
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- Biometrics, 2023, v. 79, n. 3, p. 2757, doi. 10.1111/biom.13798
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A sensitivity analysis approach for the causal hazard ratio in randomized and observational studies.
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- Biometrics, 2023, v. 79, n. 3, p. 2743, doi. 10.1111/biom.13797
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Estimating the area under the ROC curve when transporting a prediction model to a target population.
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- Biometrics, 2023, v. 79, n. 3, p. 2382, doi. 10.1111/biom.13796
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A semiparametric joint model for cluster size and subunit‐specific interval‐censored outcomes.
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- Biometrics, 2023, v. 79, n. 3, p. 2010, doi. 10.1111/biom.13795
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Latent multinomial models for extended batch‐mark data.
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- Biometrics, 2023, v. 79, n. 3, p. 2732, doi. 10.1111/biom.13789
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Improved semiparametric estimation of the proportional rate model with recurrent event data.
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- Biometrics, 2023, v. 79, n. 3, p. 1686, doi. 10.1111/biom.13788
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Joint inference for competing risks data using multiple endpoints.
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- Biometrics, 2023, v. 79, n. 3, p. 1635, doi. 10.1111/biom.13752
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CEDAR: communication efficient distributed analysis for regressions.
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- Biometrics, 2023, v. 79, n. 3, p. 2357, doi. 10.1111/biom.13786
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Statistical inference and power analysis for direct and spillover effects in two‐stage randomized experiments.
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- Biometrics, 2023, v. 79, n. 3, p. 2370, doi. 10.1111/biom.13782
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Semiparametric estimation of the transformation model by leveraging external aggregate data in the presence of population heterogeneity.
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- Biometrics, 2023, v. 79, n. 3, p. 1996, doi. 10.1111/biom.13778
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Contrasting principal stratum and hypothetical strategy estimands in multi‐period crossover trials with incomplete data.
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- Biometrics, 2023, v. 79, n. 3, p. 1896, doi. 10.1111/biom.13777
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Combining parametric and nonparametric models to estimate treatment effects in observational studies.
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- Biometrics, 2023, v. 79, n. 3, p. 1986, doi. 10.1111/biom.13776
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Identifying brain hierarchical structures associated with Alzheimer's disease using a regularized regression method with tree predictors.
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- Biometrics, 2023, v. 79, n. 3, p. 2333, doi. 10.1111/biom.13775
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Bayesian hierarchical quantile regression with application to characterizing the immune architecture of lung cancer.
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- Biometrics, 2023, v. 79, n. 3, p. 2474, doi. 10.1111/biom.13774
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Pattern‐based clustering of daily weigh‐in trajectories using dynamic time warping.
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- Biometrics, 2023, v. 79, n. 3, p. 2719, doi. 10.1111/biom.13773
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Microbiome subcommunity learning with logistic‐tree normal latent Dirichlet allocation.
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- Biometrics, 2023, v. 79, n. 3, p. 2321, doi. 10.1111/biom.13772
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How well can fine balance work for covariate balancing.
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- Biometrics, 2023, v. 79, n. 3, p. 2346, doi. 10.1111/biom.13771
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Spatial dependence modeling of latent susceptibility and time to joint damage in psoriatic arthritis.
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- Biometrics, 2023, v. 79, n. 3, p. 2605, doi. 10.1111/biom.13770
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Associating somatic mutation with clinical outcomes through kernel regression and optimal transport.
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- Biometrics, 2023, v. 79, n. 3, p. 2705, doi. 10.1111/biom.13769
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On generalized latent factor modeling and inference for high‐dimensional binomial data.
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- Biometrics, 2023, v. 79, n. 3, p. 2311, doi. 10.1111/biom.13768
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Asynchronous functional linear regression models for longitudinal data in reproducing kernel Hilbert space.
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- Biometrics, 2023, v. 79, n. 3, p. 1880, doi. 10.1111/biom.13767
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Comparing COVID‐19 incidences longitudinally per economic sector against the background of preventive measures and vaccination.
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- Biometrics, 2023, v. 79, n. 3, p. 2516, doi. 10.1111/biom.13766
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Boosting distributional copula regression.
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- Biometrics, 2023, v. 79, n. 3, p. 2298, doi. 10.1111/biom.13765
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Maximum likelihood estimation in the additive hazards model.
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- Biometrics, 2023, v. 79, n. 3, p. 1646, doi. 10.1111/biom.13764
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