[Prediction of Future Observations in Growth Curve Models]: Comment

Latent Growth Curve Models

Growth curve mixture models

doi: 10.3969/j.issn.1002-0829.2012.06.009 Division of Biostatistics, Thomas Jefferson University, Philadelphia, Pennsylvania, USA *Correspondence: [email protected] Psychiatric studies often collect longitudinal data to characterize the natural history of disease in a cohort or to evaluate the effect of behavioral or pharmaceutical interventions. For example, in a recent partially ra...

prediction of ignition delay period in d.i diesel engines

a semi-empirical mathematical model for predicting physical part of ignition delay period in the combustion of direct - injection diesel engines with swirl is developed . this model based on a single droplet evaporation model . the governing equations , namely , equations of droplet motion , heat and mass transfer were solved simultaneously using a rung-kutta step by step unmerical method . the...

Growth curve prediction from optical density data.

A fundamental aspect of predictive microbiology is the shape of the microbial growth curve and many models are used to fit microbial count data, the modified Gompertz and Baranyi equation being two of the most widely used. Rapid, automated methods such as turbidimetry have been widely used to obtain growth parameters, but do not directly give the microbial growth curve. Optical density (OD) dat...

Determination of the genetic and non-genetic variations in growth curve of Zandi lambs by random regression models

The aim of this study was to model the variances and covariances of body weight in Zandi sheep from 60 to 365 days of age using random regression models (RRM). Legendre polynomials of different orders were used to model the direct and maternal covariances. Mean trends were also modeled through a quadratic regression on orthogonal polynomials of age. Homogeneity and heterogeneity of the residual...