Copula regression spline models for binary outcomes
We introduce a framework for estimating the effect that a binary treatment has on a binary
outcome in the presence of unobserved confounding. The methodology is applied to a case …
outcome in the presence of unobserved confounding. The methodology is applied to a case …
Causal inference for comprehensive cohort studies
Y Lu, DO Scharfstein, MM Brooks, K Quach… - arXiv preprint arXiv …, 2019 - arxiv.org
In a comprehensive cohort study of two competing treatments (say, A and B), clinically
eligible individuals are first asked to enroll in a randomized trial and, if they refuse, are then …
eligible individuals are first asked to enroll in a randomized trial and, if they refuse, are then …
A Bayesian multivariate latent t-regression model for assessing the association between corticosteroid and cranial radiation exposures and cardiometabolic …
M Caubet Fernandez, S Drouin, M Samoilenko… - BMC Medical Research …, 2019 - Springer
Background Childhood acute lymphoblastic leukemia (cALL) is the most frequent pediatric
cancer. Over the past decades, treatment of cALL has significantly improved, with cure rates …
cancer. Over the past decades, treatment of cALL has significantly improved, with cure rates …
A marginalized multilevel model for bivariate longitudinal binary data
G Inan, O Ilk - Statistical Papers, 2019 - Springer
This study considers analysis of bivariate longitudinal binary data. We propose a model
based on marginalized multilevel model framework. The proposed model consists of two …
based on marginalized multilevel model framework. The proposed model consists of two …
Marginalized random-effects models for clustered binomial data through innovative link functions
I Kazemi, F Hassanzadeh - AStA Advances in Statistical Analysis, 2021 - Springer
Random-effects models are frequently used to analyze clustered binomial data. The direct
computation of the marginal mean response, when integrated over the distribution of …
computation of the marginal mean response, when integrated over the distribution of …
Bridged parametric survival models: General paradigm and speed improvements
BJ Swihart, D Bandyopadhyay - Computer methods and programs in …, 2021 - Elsevier
Background and objective: With the recent surge in availability of large biomedical
databases mostly derived from electronic health records, the need for the development of …
databases mostly derived from electronic health records, the need for the development of …
[PDF][PDF] Miguel Caubet Fernandez1, 2, Simon Drouin2, Mariia Samoilenko1, 2, Sophia Morel2, Maja Krajinovic2
Background: Childhood acute lymphoblastic leukemia (cALL) is the most frequent pediatric
cancer. Over the past decades, treatment of cALL has significantly improved, with cure rates …
cancer. Over the past decades, treatment of cALL has significantly improved, with cure rates …
[PDF][PDF] Package 'bridgedist'
B Swihart, MB Swihart - 2022 - cran.uni-muenster.de
Description An implementation of the bridge distribution with logit-link in R. In Wang and
Louis (2003)< DOI: 10.1093/biomet/90.4. 765>, such a univariate bridge distribution was …
Louis (2003)< DOI: 10.1093/biomet/90.4. 765>, such a univariate bridge distribution was …
Marginally Interpretable Generalized Linear Mixed Models
JJ Gory - 2017 - rave.ohiolink.edu
A popular approach for relating correlated measurements of a non-Gaussian response
variable to a set of predictors is to introduce latent random variables and fit a generalized …
variable to a set of predictors is to introduce latent random variables and fit a generalized …
Modelación multivariada de la pobreza multidimensional.
A Guzmán Rodríguez - 2016 - colposdigital.colpos.mx
A partir de un problema operativo sobre indicadores de pobreza en México, y una
interpretación estadística de éste; se pronone un método Bayesiano de modelación de …
interpretación estadística de éste; se pronone un método Bayesiano de modelación de …