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| Geha,Makram J.; Keown,Jeffrey F.; Van Vleck,L. Dale. |
| Milk yield records (305d, 2X, actual milk yield) of 123,639 registered first lactation Holstein cows were used to compare linear regression (y = β0 + β1X + e) ,quadratic regression, (y = β0 + β1X + β2X2 + e) cubic regression (y = β0 + β1X + β2X2 + β3X3 + e) and fixed factor models, with cubic-spline interpolation models, for estimating the effects of inbreeding on milk yield. Ten animal models, all with herd-year-season of calving as fixed effect, were compared using the Akaike corrected-Information Criterion (AICc). The cubic-spline interpolation model with seven knots had the lowest AICc, whereas for all those labeled as "traditional", AICc was higher than the best model. Results from fitting inbreeding using a cubic-spline with seven knots were compared... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Akaike's information criterion; Cubic-spline interpolation; Inbreeding; Milk yield. |
| Ano: 2011 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572011000300013 |
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| Cui, James. |
| The generalized estimating equation (GEE) approach is a widely used statistical method in the analysis of longitudinal data in clinical and epidemiological studies. It is an extension of the generalized linear model (GLM) method to correlated data such that valid standard errors of the parameter estimates can be drawn. Unlike the GLM method, which is based on the maximum likelihood theory for independent observations, the GEE method is based on the quasilikelihood theory and no assumption is made about the distribution of response observations. Therefore, Akaike’s information criterion, a widely used method for model selection in GLM, is not applicable to GEE directly. However, Pan (Biometrics 2001; 57: 120–125) proposed a model-selection method for GEE... |
| Tipo: Article |
Palavras-chave: Qic; Akaike's information criterion; GEE; Likelihood; Model; Quasilikelihood under the independence model criterion; Research Methods/ Statistical Methods. |
| Ano: 2007 |
URL: http://purl.umn.edu/119269 |
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