A Bayesian nonparametric approach to modeling longitudinal growth curves with non-normal outcomes
Longitudinal growth patterns are routinely seen in medical studies where developments of individuals on one or more outcome variables are followed over a period of time. Many current methods for modeling growth presuppose a parametric relationship between the outcome and time (e.g., linear, quadrati...
Main Author: | Kliethermes, Stephanie Ann |
---|---|
Other Authors: | Oleson, Jacob J. |
Format: | Others |
Language: | English |
Published: |
University of Iowa
2013
|
Subjects: | |
Online Access: | https://ir.uiowa.edu/etd/2546 https://ir.uiowa.edu/cgi/viewcontent.cgi?article=4675&context=etd |
Similar Items
-
Bayesian Shape Invariant growth curve model for longitudinal data
by: Bhuiyan, Mohammad AN
Published: (2019) -
Bayesian nonparametric analysis of longitudinal data with non-ignorable non-monotone missingness
by: Cao, Yu
Published: (2019) -
Monotone spline-based nonparametric estimation of longitudinal data with mixture distributions
by: Lu, Wenjing
Published: (2016) -
Bayesian Inference on Longitudinal Semi-continuous Substance Abuse/Dependence Symptoms Data
by: Xing, Dongyuan
Published: (2015) -
Bayesian modeling of neuropsychological test scores
by: Du, Mengtian
Published: (2021)