✦ LIBER ✦

Random Regression Models for Male and Female Fertility Evaluation Using Longitudinal Binary Data

✍ Scribed by T. Averill; R. Rekaya; K. Weigel

Book ID: 117977106
Publisher: American Dairy Science Association
Year: 2006
Tongue: English
Weight: 197 KB
Volume: 89
Category: Article
ISSN: 0022-0302
DOI: 10.3168/jds.s0022-0302(06)72408-0

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Genetic Analysis of Male and Female Fert

Genetic Analysis of Male and Female Fertility Using Longitudinal Binary Data

✍ T.A. Averill; R. Rekaya; K. Weigel 📂 Article 📅 2004 🏛 American Dairy Science Association 🌐 English ⚖ 126 KB

Marginalized transition random effect mo

Marginalized transition random effect models for multivariate longitudinal binary data

✍ Ozlem Ilk; Michael J. Daniels 📂 Article 📅 2007 🏛 John Wiley and Sons 🌐 French ⚖ 223 KB 👁 2 views

## Abstract Generalized linear models with random effects and/or serial dependence are commonly used to analyze longitudinal data. However, the computation and interpretation of marginal covariate effects can be difficult. This led Heagerty (1999, 2002) to propose models for longitudinal binary dat

Genetic evaluation of dairy cattle for c

Genetic evaluation of dairy cattle for conformation traits using random regression models

✍ H. Uribe; L. R. Schaeffer; J. Jamrozik; T. J. Lawlor 📂 Article 📅 2008 🏛 John Wiley and Sons 🌐 English ⚖ 155 KB

31A Tracking in random regression mixed

31A Tracking in random regression mixed models for longitudinal data: Graphical examination and comparison of BLUP and OLS procedures

✍ Ronald W. Helms; Russell W. Helms 📂 Article 📅 1995 🏛 Elsevier Science 🌐 English ⚖ 61 KB

Estimating herd-specific force of infect

Estimating herd-specific force of infection by using random-effects models for clustered binary data and monotone fractional polynomials

✍ Christel Faes; Niel Hens; Marc Aerts; Ziv Shkedy; Helena Geys; Koen Mintiens; Ha 📂 Article 📅 2006 🏛 John Wiley and Sons 🌐 English ⚖ 964 KB

Using synthetic data to evaluate multipl

Using synthetic data to evaluate multiple regression and principal component analyses for statistical modeling of daily building energy consumption

✍ T.A. Reddy; D.E. Claridge 📂 Article 📅 1994 🏛 Elsevier Science 🌐 English ⚖ 923 KB

Multiple regression modeling of monitored building energy use data is often faulted as a reliable means of predicting energy use on the grounds that multicollinearity between the regressor variables can lead both to improper interpretation of the relative importance of the various physical regressor