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Correlated geometric models of order k and its application to intensive care unit and leprosy data
Correlated geometric models of order k and its application to intensive care unit and leprosy data
Geometric models are used to analyse the discrete time until the occurrence of an event of interest (success or consecutiv...
Statistical considerations for cross‐sectional HIV incidence estimation based on recency test
Statistical considerations for cross‐sectional HIV incidence estimation based on recency test
Abstract Longitudinal cohorts to determine the incidence of HIV infection are logistically challenging, so researchers hav...
Sample size calculation in hierarchical 2×2 factorial trials with unequal cluster sizes
Sample size calculation in hierarchical 2×2 factorial trials with unequal cluster sizes
Motivated by a suicide prevention trial with hierarchical treatment allocation (cluster-level and individual-level treatme...
Practical recommendations on double score matching for estimating causal effects
Practical recommendations on double score matching for estimating causal effects
Unlike in randomized clinical trials (RCTs), confounding control is critical for estimating the causal effects from observ...
An extension of the mixed‐effects growth model that considers between‐person differences in the within‐subject variance and the autocorrelation
An extension of the mixed‐effects growth model that considers between‐person differences in the within‐subject variance and the autocorrelation
Experience sampling methods have led to a significant increase in the availability of intensive longitudinal data. Typical...
Ranked set sampling in finite populations with bivariate responses: An application to an osteoporosis study
Ranked set sampling in finite populations with bivariate responses: An application to an osteoporosis study
The majority of the research on rank-based sampling designs in finite populations has been concerned with univariate situa...
Accounting for unequal cluster sizes in designing cluster randomized trials to detect treatment effect heterogeneity
Accounting for unequal cluster sizes in designing cluster randomized trials to detect treatment effect heterogeneity
Abstract Unequal cluster sizes are common in cluster randomized trials (CRTs). While there are a number of previous invest...
Minimum sample size calculations for external validation of a clinical prediction model with a time‐to‐event outcome
Minimum sample size calculations for external validation of a clinical prediction model with a time‐to‐event outcome
Abstract Previous articles in Statistics in Medicine describe how to calculate the sample size required for external valid...
Complex survival trial design by the product integration method
Complex survival trial design by the product integration method
Nonproportional hazards (NPHs) are often observed in survival trials such as the immunotherapy cancer trials. Under NPH, t...
Multivariate log‐contrast regression with sub‐compositional predictors: Testing the association between preterm infants' gut microbiome and neurobehavioral outcomes
Multivariate log‐contrast regression with sub‐compositional predictors: Testing the association between preterm infants' gut microbiome and neurobehavioral outcomes
To link a clinical outcome with compositional predictors in microbiome analysis, the linear log-contrast model is a popula...
Bayesian regularization for a nonstationary Gaussian linear mixed effects model
Bayesian regularization for a nonstationary Gaussian linear mixed effects model
In omics experiments, estimation and variable selection can involve thousands of proteins/genes observed from a relatively...
A puzzle of proportions: Two popular Bayesian tests can yield dramatically different conclusions
A puzzle of proportions: Two popular Bayesian tests can yield dramatically different conclusions
Testing the equality of two proportions is a common procedure in science, especially in medicine and public health. In the...
Risk prediction models for discrete ordinal outcomes: Calibration and the impact of the proportional odds assumption
Risk prediction models for discrete ordinal outcomes: Calibration and the impact of the proportional odds assumption
Abstract Calibration is a vital aspect of the performance of risk prediction models, but research in the context of ordina...
Determination of the number of observers needed to evaluate a subjective test and its application in two PD‐L1 studies
Determination of the number of observers needed to evaluate a subjective test and its application in two PD‐L1 studies
In pathological studies, subjective assays, especially companion diagnostic tests, can dramatically affect treatment of ca...
Estimation and inference for multikink expectile regression with longitudinal data
Estimation and inference for multikink expectile regression with longitudinal data
In this article, we investigate parameter estimation, kink points testing and statistical inference for a longitudinal mul...
Bayesian multivariate network meta‐analysis model for the difference in restricted mean survival times
Bayesian multivariate network meta‐analysis model for the difference in restricted mean survival times
Abstract Network meta-analysis (NMA) is essential for clinical decision-making. NMA enables inference for all pair-wise co...
Predicting outcomes of phase III oncology trials with Bayesian mediation modeling of tumor response
Predicting outcomes of phase III oncology trials with Bayesian mediation modeling of tumor response
Pivotal cancer trials often fail to yield evidence in support of new therapies thought to offer promising alternatives to ...
Marginal indirect standardization using latent clustering on multiple hospitals
Marginal indirect standardization using latent clustering on multiple hospitals
A method was introduced in 2018 of performing indirect standardization for hospital profiling when only the marginal distr...
Methods to assess evidence consistency in dose‐response model based network meta‐analysis
Methods to assess evidence consistency in dose‐response model based network meta‐analysis
Abstract Network meta-analysis (NMA) simultaneously estimates multiple relative treatment effects based on evidence that f...
Conditional Gaussian graphical model for estimating personalized disease symptom networks
Conditional Gaussian graphical model for estimating personalized disease symptom networks
The co-occurrence of symptoms may result from the direct interactions between these symptoms and the symptoms can be treat...
Extending Hui‐Walter framework to correlated outcomes with application to diagnosis tests of an eye disease among premature infants
Extending Hui‐Walter framework to correlated outcomes with application to diagnosis tests of an eye disease among premature infants
Abstract Diagnostic accuracy, a measure of diagnostic tests for correctly identifying patients with or without a target di...
Bayesian transformation models with partly interval‐censored data
Bayesian transformation models with partly interval‐censored data
In many scientific fields, partly interval-censored data, which consist of exactly observed and interval-censored observat...
BIPSE: A biomarker‐based phase I/II design for immunotherapy trials with progression‐free survival endpoint
BIPSE: A biomarker‐based phase I/II design for immunotherapy trials with progression‐free survival endpoint
Abstract A Bayesian biomarker-based phase I/II design (BIPSE) is presented for immunotherapy trials with a progression-fre...
Feature selection and classification over the network with missing node observations
Feature selection and classification over the network with missing node observations
Abstract Jointly analyzing transcriptomic data and the existing biological networks can yield more robust and informative ...
Event‐specific win ratios for inference with terminal and non‐terminal events
Event‐specific win ratios for inference with terminal and non‐terminal events
Abstract For semi-competing risks data involving a non-terminal event and a terminal event we derive the asymptotic distri...
A semiparametric Gumbel regression model for analyzing longitudinal data with non‐normal tails
A semiparametric Gumbel regression model for analyzing longitudinal data with non‐normal tails
Abnormal longitudinal values in biomarkers can be a sign of abnormal status or signal development of a disease. Identifyin...
A conditional autoregressive model for genetic association analysis accounting for genetic heterogeneity
A conditional autoregressive model for genetic association analysis accounting for genetic heterogeneity
Abstract Converging evidence from genetic studies and population genetics theory suggest that complex diseases are charact...
Using fractional polynomials and restricted cubic splines to model non‐proportional hazards or time‐varying covariate effects in the Cox regression model
Using fractional polynomials and restricted cubic splines to model non‐proportional hazards or time‐varying covariate effects in the Cox regression model
Abstract The Cox proportional hazards model is used extensively in clinical and epidemiological research. A key assumption...
A semiparametric risk score for physical activity
A semiparametric risk score for physical activity
We develop a generalized partially additive model to build a single semiparametric risk scoring system for physical activi...
Improving main analysis by borrowing information from auxiliary data
Improving main analysis by borrowing information from auxiliary data
In many clinical and observational studies, auxiliary data from the same subjects, such as repeated measurements or surrog...
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