Description

A dataset simulated using methods described in the reference below.

Reference: Chow, S., Lu, Z., Sherwood, A., and Zhu, H. (2016). Fitting Nonlinear Ordinary Differential Equation Models with Random Effects and Unknown Initial Conditions Using the Stochastic Approximation Expectation-Maximization (SAEM) Algorithm. Psychometrika, 81(1), 102-134.

Usage

Format

A data frame with 10,000 rows and 11 variables

Details

The variables are as follows:

• batch. Batch number from simulation

• kk. Unclear

• trueInit. True initial condition

• id. Person ID

• time. Continuous time of measurement

• y1. Observed score 1

• y2. Observed score 2

• y3. Observed score 3

• u1. Covariate 1

• u2. Covariate 2

• trueb. True value of person-specific random effect