Pages that link to "Item:Q5715353"
From MaRDI portal
The following pages link to A Flexible B‐Spline Model for Multiple Longitudinal Biomarkers and Survival (Q5715353):
Displaying 50 items.
- Stochastic model for analysis of longitudinal data on aging and mortality (Q97673) (← links)
- Fast fitting of joint models for longitudinal and event time data using a pseudo-adaptive Gaussian quadrature rule (Q425636) (← links)
- An approach for jointly modeling multivariate longitudinal measurements and discrete time-to-event data (Q614171) (← links)
- Missing data methods in longitudinal studies: a review (Q619079) (← links)
- A more flexible joint latent model for longitudinal and survival time data (Q626415) (← links)
- Predictive comparison of joint longitudinal-survival modeling: a case study illustrating competing approaches (Q746087) (← links)
- Bayesian local influence for survival models (Q746090) (← links)
- Bayesian regression analysis of data with random effects covariates from nonlinear longitudinal measurements (Q900794) (← links)
- Assessing the association between trends in a biomarker and risk of event with an application in pediatric HIV/AIDS (Q985033) (← links)
- Semiparametric Bayesian joint models of multivariate longitudinal and survival data (Q1623585) (← links)
- Dynamic survival models with varying coefficients for credit risks. (Q1711479) (← links)
- A Bayesian inference for the penalized spline joint models of longitudinal and time-to-event data: a prior sensitivity analysis (Q1985373) (← links)
- Consistent estimation of a joint model for multivariate longitudinal and survival data with latent variables (Q2057836) (← links)
- Joint models with multiple longitudinal outcomes and a time-to-event outcome: a corrected two-stage approach (Q2195844) (← links)
- Joint model-based clustering of nonlinear longitudinal trajectories and associated time-to-event data analysis, linked by latent class membership: with application to AIDS clinical studies (Q2274652) (← links)
- Quantile regression-based Bayesian joint modeling analysis of longitudinal-survival data, with application to an AIDS cohort study (Q2308441) (← links)
- Functional approach of flexibly modelling generalized longitudinal data and survival time (Q2474384) (← links)
- Free Knot Splines with RJMCMC in Survival Data Analysis (Q2786249) (← links)
- A Bayesian joint model of menstrual cycle length and fecundity (Q2805197) (← links)
- Joint modeling of multivariate longitudinal mixed measurements and time to event data using a Bayesian approach (Q2953255) (← links)
- Joint modeling of multivariate censored longitudinal and event time data with application to the Genetic Markers of Inflammation Study (Q2953281) (← links)
- Joint modelling of longitudinal and time-to-event data with application to predicting abdominal aortic aneurysm growth and rupture (Q3100760) (← links)
- Dynamic Predictions and Prospective Accuracy in Joint Models for Longitudinal and Time-to-Event Data (Q3100782) (← links)
- Joint monitoring and prediction of accrual and event times in clinical trials (Q3145573) (← links)
- A Kernel Smooth Approach for Joint Modeling of Accelerated Failure Time and Longitudinal Data (Q3178529) (← links)
- Assessing importance of biomarkers: A Bayesian joint modelling approach of longitudinal and survival data with semi-competing risks (Q3389290) (← links)
- Modeling Longitudinal Data with Nonparametric Multiplicative Random Effects Jointly with Survival Data (Q3506505) (← links)
- Semiparametric Modeling of Longitudinal Measurements and Time‐to‐Event Data–A Two‐Stage Regression Calibration Approach (Q3549419) (← links)
- Bayesian Influence Measures for Joint Models for Longitudinal and Survival Data (Q4649077) (← links)
- Flexible methods for analysing longitudinal data using piecewise cubic polynomials (Q4869589) (← links)
- A flexible bimodal model with long-term survivors and different regression structures (Q5083885) (← links)
- Joint modeling of longitudinal count and time-to-event data with excess zero using accelerated failure time model: an application with CD4 cell counts (Q5104526) (← links)
- Joint modeling of censored longitudinal and event time data (Q5128883) (← links)
- Segmental modeling of changing immunologic response for CD4 data with skewness, missingness and dropout (Q5129108) (← links)
- Joint modelling of longitudinal and repeated time-to-event data using nonlinear mixed-effects models and the stochastic approximation expectation–maximization algorithm (Q5220804) (← links)
- Joint models for multiple longitudinal processes and time-to-event outcome (Q5221561) (← links)
- Joint penalized spline modeling of multivariate longitudinal data, with application to HIV‐1 RNA load levels and CD4 cell counts (Q6052230) (← links)
- A flexible joint model for multiple longitudinal biomarkers and a time‐to‐event outcome: With applications to dynamic prediction using highly correlated biomarkers (Q6068288) (← links)
- Dynamic monitoring of the effects of adherence to medication on survival in heart failure patients: A joint modeling approach exploiting time‐varying covariates (Q6071298) (← links)
- Joint models of multivariate longitudinal outcomes and discrete survival data with INLA: an application to credit repayment behaviour (Q6168507) (← links)
- Smoothing exponential-polynomial splines for multiexponential decay data (Q6557285) (← links)
- Joint mixed membership modeling of multivariate longitudinal and survival data for learning the individualized disease progression (Q6616333) (← links)
- Joint modeling of multistate and nonparametric multivariate longitudinal data (Q6616397) (← links)
- Individualized dynamic prediction of survival with the presence of intermediate events (Q6627214) (← links)
- A Bayesian joint model for zero-inflated integers and left-truncated event times with a time-varying association: applications to senior health care (Q6627873) (← links)
- Joint modeling of multivariate nonparametric longitudinal data and survival data: a local smoothing approach (Q6628209) (← links)
- Modeling the underlying biological processes in Alzheimer's disease using a multivariate competing risk joint model (Q6628645) (← links)
- A marginal estimate for the overall treatment effect on a survival outcome within the joint modeling framework (Q6629873) (← links)
- Joint models of longitudinal and time-to-event data with more than one event time outcome: a review (Q6636164) (← links)
- A copula model for marked point process with a terminal event: an application in dynamic prediction of insurance claims (Q6665456) (← links)
