40.2k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of CincinnatiUS19 papers
- University of Cincinnati Medical CenterUS8 papers
- University of PennsylvaniaUS4 papers
- Children's Hospital of PhiladelphiaUS3 papers
- Harvard UniversityUS3 papers
- Rutgers, The State University of New JerseyUS3 papers
- University of California, Los AngelesUS3 papers
- University of California San DiegoUS3 papers
- University of CambridgeGB3 papers
- University of Wisconsin–MadisonUS3 papers
- Yale UniversityUS3 papers
- Amrita Vishwa VidyapeethamIN2 papers
7 papers · 1 filter
A Bayesian location-scale joint model for time-to-event and multivariate longitudinal data with association based on within-individual variability
Marco Palma, Ruth H Keogh, Siobhán B Carr +5
Within-individual variability of health indicators measured over time is becoming commonly used to inform about disease progression. Simple summary statistics (e.g. the standard de…
A joint model for (un)bounded longitudinal markers, competing risks, and recurrent events using patient registry data
Pedro Miranda Afonso, Dimitris Rizopoulos, Anushka K. Palipana +5
Joint models for longitudinal and survival data have become a popular framework for studying the association between repeatedly measured biomarkers and clinical events. Nevertheles…
Bayesian Shape Invariant Model for Latent Growth Curve with Time-Invariant Covariates
Mohammad Alfrad Nobel Bhuiyan, Heidi Sucharew, Rhonda Szczesniak +4
In the attention-deficit hyperactivity disorder (ADHD) study, children are prescribed different stimulant medications. The height measurements are recorded longitudinally along wit…
Efficiency of Observed Information Adaptive Designs
Adam Lane
In this work the primary objective is to maximize the precision of the maximum likelihood estimate in a linear regression model through the efficient design of the experiment. One…
Conditional Information and Inference in Response-Adaptive Allocation Designs
Adam Lane
Response-adaptive allocation designs refer to a class of designs where the probability an observation is assigned to a treatment is changed throughout an experiment based on the ac…
GPMatch: A Bayesian Doubly Robust Approach to Causal Inference with Gaussian Process Covariance Function As a Matching Tool
Bin Huang, Chen Chen, Jinzhong Liu
Gaussian process (GP) covariance function is proposed as a matching tool in GPMatch within a full Bayesian framework under relatively weaker causal assumptions. The matching is acc…
Adaptive Designs for Optimal Observed Fisher Information
Adam Lane
Expected Fisher information can be found a priori and as a result its inverse is the primary variance approximation used in the design of experiments. This is in contrast to the co…