32 citations · 46 across the 10 of their papers we have counts for
11 papers
Pseudo-value regression of clustered multistate current status data with informative cluster sizes
Samuel Anyaso-Samuel, Dipankar Bandyopadhyay, Somnath Datta
Multistate current status (CS) data presents a more severe form of censoring due to the single observation of study participants transitioning through a sequence of well-defined di…
Efficient Estimation of the Additive Risks Model for Interval-Censored Data
Tong Wang, Dipankar Bandyopadhyay, Samiran Sinha
In contrast to the popular Cox model which presents a multiplicative covariate effect specification on the time to event hazards, the semiparametric additive risks model (ARM) offe…
Alleviating Spatial Confounding in Spatial Frailty Models
Douglas Roberto Mesquita Azevedo, Marcos Oliveira Prates, Dipankar Bandyopadhyay
Spatial confounding is how is called the confounding between fixed and spatial random effects. It has been widely studied and it gained attention in the past years in the spatial s…
Efficient Estimation of Mixture Cure Frailty Model for Clustered Current Status Data
Tong Wang, Kejun He, Wei Ma +2
Current status data abounds in the field of epidemiology and public health, where the only observable data for a subject is the random inspection time and the event status at inspe…
A Spatial Bayesian Semiparametric Mixture Model for Positive Definite Matrices with Applications to Diffusion Tensor Imaging
Zhou Lan, Brian J. Reich, Dipankar Bandyopadhyay
Diffusion tensor imaging (DTI) is a popular magnetic resonance imaging technique used to characterize microstructural changes in the brain. DTI studies quantify the diffusion of wa…
SMARTp: A SMART design for non-surgical treatments of chronic periodontitis with spatially-referenced and non-randomly missing skewed outcomes
Jing Xu, Dipankar Bandyopadhyay, Sedigheh Mirzaei +2
This paper proposes dynamic treatment regimes for choosing individualized effective treatment strategies of chronic periodontal disease. R codes for implementing the proposed sampl…
BAREB: A Bayesian repulsive biclustering model for periodontal data
Yuliang Li, Dipankar Bandyopadhyay, Fangzheng Xie +1
Preventing periodontal diseases (PD) and maintaining the structure and function of teeth are important goals for personal oral care. To understand the heterogeneity in patients wit…
Bayesian nonparametric multiway regression for clustered binomial data
Eric F. Lock, Dipankar Bandyopadhyay
We introduce a Bayesian nonparametric regression model for data with multiway (tensor) structure, motivated by an application to periodontal disease (PD) data. Our outcome is the n…
Bayesian Nonparametric Policy Search with Application to Periodontal Recall Intervals
Qian Guan, Brian J. Reich, Eric B. Laber +1
Tooth loss from periodontal disease is a major public health burden in the United States. Standard clinical practice is to recommend a dental visit every six months; however, this…
Changing approaches of prosecutors towards juvenile repeated sex-offenders: A Bayesian evaluation
Dipankar Bandyopadhyay, Debajyoti Sinha, Stuart Lipsitz +1
Existing state-wide data bases on prosecutors' decisions about juvenile offenders are important, yet often un-explored resources for understanding changes in patterns of judicial d…
A latent factor model for spatial data with informative missingness
Brian J. Reich, Dipankar Bandyopadhyay
A large amount of data is typically collected during a periodontal exam. Analyzing these data poses several challenges. Several types of measurements are taken at many locations th…