A Bayesian Model for Growth Curve Analysis

June 1, 1995Biometrics

View at Publisher

Ask AI

Bookmark

Share

Key Points

This research aims to estimate a function describing growth curves using a Bayesian model and test the homogeneity of these functions across subjects.
Analyzed data from K subjects with observed values of random variable Y at specified times.
Modeled the function as a Gaussian process and implemented posterior mean estimation for function F(i, t).
Developed a test for the homogeneity hypothesis and used Monte Carlo simulations to validate the methodology.
The proposed Bayesian method effectively estimates the growth curve functions, demonstrating similarity across subjects.
The posterior mean provided a reliable estimate for the growth curve with varying temperature and blood pressure.
Monte Carlo simulations confirmed the robustness and effectiveness of the new methodology for curve estimation.

Answers are grounded in this paper and cite their sources.

Demonstrates growth curve analysis for temperature and blood pressure variations, suggesting effective Bayesian modeling methods.

No abstract yet. The journal hasn't published one we can show.

No takes yet. Share an insight, caveat, or question.

D. T. Barry (1995) studied this question.

View at Publisher

Ask AI

Bookmark

Share