Longitudinal data

Estimation of genetic parameters for partial egg production periods by means of random regression models

G. C. Venturini, Grossi, D. A., Ramos, S. B., Cruz, V. A. R., Souza, C. G., Ledur, M. C., L. Faro, E., Schmidt, G. S., and Munari, D. P., “Estimation of genetic parameters for partial egg production periods by means of random regression models”, vol. 11, pp. 1819-1829, 2012.

We estimated genetic parameters for egg production in different periods by means of random regression models, aiming at selection based on partial egg production from a generation of layers. The production was evaluated for each individual by recording the number of eggs produced from 20 to 70 weeks of age, with partial records taken every three weeks for a total of 17 periods. The covariance functions were estimated with a random regression model by the restricted maximum likelihood method.

Genetic analysis of longitudinal data in beef cattle: a review

S. E. Speidel, Enns, R. M., and Crews, Jr., D. H., “Genetic analysis of longitudinal data in beef cattle: a review”, vol. 9. pp. 19-33, 2010.

Currently, many different data types are collected by beef cattle breed associations for the purpose of genetic evaluation. These data points are all biological characteristics of individual animals that can be measured multiple times over an animal´s lifetime. Some traits can only be measured once on an individual animal, whereas others, such as the body weight of an animal as it grows, can be measured many times.