Generalized linear mixed models for the genetic evaluation of binary reproductive traits: a simulation study

The objective of this study was to evaluate the use of probit and logit link functions for the genetic evaluation of early pregnancy using simulated data. The following simulation/analysis structures were constructed: logit/logit, logit/probit, probit/logit, and probit/probit. The percentages of precocious females were 5, 10, 15, 20, 25 and 30% and were adjusted based on a change in the mean of the latent variable. The parametric heritability (h²) was 0.40. Simulation and genetic evaluation were implemented in the R software. Heritability estimates (ĥ²) were compared with h² using the mean squared error. Pearson correlations between predicted and true breeding values and the percentage of coincidence between true and predicted ranking, considering the 10% of bulls with the highest breeding values (TOP10) were calculated. The mean ĥ² values were under- and overestimated for all percentages of precocious females when logit/probit and probit/logit models used. In addition, the mean squared errors of these models were high when compared with those obtained with the probit/probit and logit/logit models. Considering ĥ², probit/probit and logit/logit were also superior to logit/probit and probit/logit, providing values close to the parametric heritability. Logit/probit and probit/logit presented low Pearson correlations, whereas the correlations obtained with probit/probit and logit/logit ranged from moderate to high. With respect to the TOP10 bulls, logit/probit and probit/logit presented much lower percentages than probit/probit and logit/logit. The genetic parameter estimates and predictions of breeding values of the animals obtained with the logit/logit and probit/probit models were similar. In contrast, the results obtained with probit/logit and logit/probit were not satisfactory. There is need to compare the estimation and prediction ability of logit and probit link functions.

Random regression models using different functions to model test-day milk yield of Brazilian Holstein cows

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The highest intensity and the shortest duration permitting attainment of maximal oxygen uptake during cycling: effects of different methods and aerobic fitness level

The aims of this study were: (1) to verify the validity of previous proposed models to estimate the lowest exercise duration (T (LOW)) and the highest intensity (I (HIGH)) at which VO(2)max is reached (2) to test the hypothesis that parameters involved in these models, and hence the validity of these models are affected by aerobic training status. Thirteen cyclists (EC), eleven runners (ER) and ten untrained (U) subjects performed several cycle-ergometer exercise tests to fatigue in order to determine and estimate T (LOW) (ET (LOW)) and I (HIGH) (EI (HIGH)). The relationship between the time to achieved VO(2)max and time to exhaustion (T (lim)) was used to estimate ET (LOW). EI (HIGH) was estimated using the critical power model. I (HIGH) was assumed as the highest intensity at which VO2 was equal or higher than the average of VO(2)max values minus one typical error. T (LOW) was considered T (lim) associated with I (HIGH). No differences were found in T (LOW) between ER (170 +/- 31 s) and U (209 +/- 29 s), however, both showed higher values than EC (117 +/- 29 s). I (HIGH) was similar between U (269 +/- 73 W) and ER (319 +/- 50 W), and both were lower than EC (451 +/- 33 W). EI (HIGH) was similar and significantly correlated with I-HIGH only in U (r = 0.87) and ER (r = 0.62). ET (LOW) and T (LOW) were different only for U and not significantly correlated in all groups. These data suggest that the aerobic training status affects the validity of the proposed models for estimating I (HIGH).

Quantidade e Duração Silábicas em Português do Brasil

Análise das relações existentes entre as predições dos modelos fonológicos não-lineares (em especial, o de Hayes, 1995) a respeito da quantidade das sílabas e a efetiva realização fonética dessas sílabas em termos de duração, através da consideração de dados extraídos do Projeto Gramática do Português Falado.

Methods to verify parameter equality in nonlinear regression models

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Fluoride dose response in pH-cycling models using bovine enamel

The aim of this study was to establish methodologies for verification of the fluoride solution dose-response relationship using bovine enamel and pH-cycling models. Six models of the cariogenic challenge were performed, varying the time of demineralization and pH, time of remineralization, composition of de- and remineralization solutions, frequency and time of application of treatment solutions and pH-cycling duration. For the evaluation of the fluoride effect on caries dynamics, two proposed models provided for improvement in standardization of methods leading to a higher level of precision, demonstrating a dose response between treatments with regard to surface microhardness and Delta Z. For the evaluation of the fluoride effect on enamel remineralization, the addition of fluoride to the de- and remineralization solutions and the reduction of frequency and time of application of fluoride solutions led to a more suitable pH-cycling model. Copyright (C) 2005 S. Karger AG, Basel.

Progression of liver fibrosis in blood donors infected with hepatitis C virus

Background/Aims. Chronic hepatitis by HCV is progressive towards cirrhosis, with variable rate. We evaluated the rate of fibrosis progression (RFP), risk factors associated with advanced fibrosis (F3 and F4), and estimated the evolution time to cirrhosis. Methods. We transversely selected 142 blood donors infected only with HCV, with a known route of infection, submitted to liver biopsy at admission. RFP= ratio between stage of fibrosis (METAVIR)/estimated duration of infection in years. Non-parametric tests and logistic regression analysis, with significance level of 5% were used. Results. Median RFP was 0.086 U/year (0.05 - 0.142). Ten patients had F4 and 25 had F3. Median RFP values were significantly different (p=0.001) from one age group at contamination to the others and ALT and AST levels. There were no differences in the expected evolution to cirrhosis between intermediate fibrosers (F2) and the rapid fibrosers (F3 and F4). The independent variables associated with advanced fibrosis were ALT (OR 7.2) and GGT (OR 6.4) and age at inclusion (OR 1.12). Conclusion. This study suggests that RFP is extremely variable, it is exponential with age, and mainly influenced by host characteristics, especially age at contamination and possibly ethnical group. These asymptomatic patients had high percentage of fibrosis F2, F3 and F4.

Fractional polynomial response surface models

Second-order polynomial models have been used extensively to approximate the relationship between a response variable and several continuous factors. However, sometimes polynomial models do not adequately describe the important features of the response surface. This article describes the use of fractional polynomial models. It is shown how the models can be fitted, an appropriate model selected, and inference conducted. Polynomial and fractional polynomial models are fitted to two published datasets, illustrating that sometimes the fractional polynomial can give as good a fit to the data and much more plausible behavior between the design points than the polynomial model. © 2005 American Statistical Association and the International Biometric Society.

Estimates of covariance functions for growth of Nelore cattle applying a parametric correlation structure to model within-animal correlations

A total of 20,065 weights recorded on 3016 Nelore animals were used to estimate covariance functions for growth from birth to 630 days of age, assuming a parametric correlation structure to model within-animal correlations. The model of analysis included fixed effects of contemporary groups and age of dam as quadratic covariable. Mean trends were taken into account by a cubic regression on orthogonal polynomials of animal age. Genetic effects of the animal and its dam and maternal permanent environmental effects were modelled by random regressions on Legendre polynomials of age at recording. Changes in direct permanent environmental effect variances were modelled by a polynomial variance function, together with a parametric correlation function to account for correlations between ages. Stationary and nonstationary models were used to model within-animal correlations between different ages. Residual variances were considered homogeneous or heterogeneous, with changes modelled by a step or polynomial function of age at recording. Based on Bayesian information criterion, a model with a cubic variance function combined with a nonstationary correlation function for permanent environmental effects, with 49 parameters to be estimated, fitted best. Modelling within-animal correlations through a parametric correlation structure can describe the variation pattern adequately. Moreover, the number of parameters to be estimated can be decreased substantially compared to a model fitting random regression on Legendre polynomial of age. © 2004 Elsevier B.V. All rights reserved.

Analysis of culling probability in dairy buffalo using survival models

In order to contribute to the genetic breeding programs of buffaloes, this study aimed to determine the influence of environmental effects on the stayability (ST) of dairy female Murrah buffalo in the herd. Data from 1016 buffaloes were used. ST was defined as the ability of the female to remain in the herd for 1, 2, 3, 4, 5 or 6 years after the first calving. Environmental effects were studied by survival analysis, adjusted to the fixed effects of farm, year and season of birth, class of first-lactation milk yield and age at first calving. The data were analyzed using the LIFEREG procedure of the SAS program that fits parametric models to failure time data (culling or ST = 0), and estimates parameters by maximum likelihood estimation. Breeding farm, year of birth and first-lactation milk yield significantly influenced (P < 0.0001) the ST to the specific ages (1 to 6 years after the first calving). Buffaloes that were older at first calving presented higher probabilities of being culled 1 year after the first calving, without any effect on culling at older ages. Buffaloes with a higher milk yield at first calving presented a lower culling probability and remained for a longer period of time in the herd. The effects of breeding farm, year of birth and first-lactation milk yield should be included in models used for the analysis of ST in buffaloes. Copyright © The Animal Consortium 2010.

Comparison of random regression models to estimate genetic parameters for milk production in Guzerat (Bos indicus) cows

Random regression models have been widely used to estimate genetic parameters that influence milk production in Bos taurus breeds, and more recently in B. indicus breeds. With the aim of finding appropriate random regression model to analyze milk yield, different parametric functions were compared, applied to 20,524 test-day milk yield records of 2816 first-lactation Guzerat (B. indicus) cows in Brazilian herds. The records were analyzed by random regression models whose random effects were additive genetic, permanent environmental and residual, and whose fixed effects were contemporary group, the covariable cow age at calving (linear and quadratic effects), and the herd lactation curve. The additive genetic and permanent environmental effects were modeled by the Wilmink function, a modified Wilmink function (with the second term divided by 100), a function that combined third-order Legendre polynomials with the last term of the Wilmink function, and the Ali and Schaeffer function. The residual variances were modeled by means of 1, 4, 6, or 10 heterogeneous classes, with the exception of the last term of the Wilmink function, for which there were 1, from 0.20 to 0.33. Genetic correlations between adjacent records were high values (0.83-0.99), but they declined when the interval between the test-day records increased, and were negative between the first and last records. The model employing the Ali and Schaeffer function with six residual variance classes was the most suitable for fitting the data. © FUNPEC-RP.

Metodologia para determinar a relação dose-resposta de produtos fluoretados utilizando esmalte bovino e modelo de ciclagem de pH

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Predicting breeding values for milk yield of Guzera (Bos indicus) cows using random regression models

Given the importance of Guzera breeding programs for milk production in the tropics, the objective of this study was to compare alternative random regression models for estimation of genetic parameters and prediction of breeding values. Test-day milk yields records (TDR) were collected monthly, in a maximum of 10 measurements. The database included 20,524 records of first lactation from 2816 Guzera cows. TDR data were analyzed by random regression models (RRM) considering additive genetic, permanent environmental and residual effects as random and the effects of contemporary group (CG), calving age as a covariate (linear and quadratic effects) and mean lactation curve as fixed. The genetic additive and permanent environmental effects were modeled by RRM using Wilmink, All and Schaeffer and cubic B-spline functions as well as Legendre polynomials. Residual variances were considered as heterogeneous classes, grouped differently according to the model used. Multi-trait analysis using finite-dimensional models (FDM) for testday milk records (TDR) and a single-trait model for 305-days milk yields (default) using the restricted maximum likelihood method were also carried out as further comparisons. Through the statistical criteria adopted, the best RRM was the one that used the cubic B-spline function with five random regression coefficients for the genetic additive and permanent environmental effects. However, the models using the Ali and Schaeffer function or Legendre polynomials with second and fifth order for, respectively, the additive genetic and permanent environmental effects can be adopted, as little variation was observed in the genetic parameter estimates compared to those estimated by models using the B-spline function. Therefore, due to the lower complexity in the (co)variance estimations, the model using Legendre polynomials represented the best option for the genetic evaluation of the Guzera lactation records. An increase of 3.6% in the accuracy of the estimated breeding values was verified when using RRM. The ranks of animals were very close whatever the RRM for the data set used to predict breeding values. Considering P305, results indicated only small to medium difference in the animals' ranking based on breeding values predicted by the conventional model or by RRM. Therefore, the sum of all the RRM-predicted breeding values along the lactation period (RRM305) can be used as a selection criterion for 305-day milk production. (c) 2014 Elsevier B.V. All rights reserved.

Different bacterial models for in vitro induction of non-cavitated enamel caries-like lesions: microhardness and polarized light miscroscopy analyses

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Response plateau models fitting via isotonic regression

Within the nutritional context, the supplementation of microminerals in bird food is often made in quantities exceeding those required in the attempt to ensure the proper performance of the animals. The experiments of type dosage x response are very common in the determination of levels of nutrients in optimal food balance and include the use of regression models to achieve this objective. Nevertheless, the regression analysis routine, generally, uses a priori information about a possible relationship between the response variable. The isotonic regression is a method of estimation by least squares that generates estimates which preserves data ordering. In the theory of isotonic regression this information is essential and it is expected to increase fitting efficiency. The objective of this work was to use an isotonic regression methodology, as an alternative way of analyzing data of Zn deposition in tibia of male birds of Hubbard lineage. We considered the models of plateau response of polynomial quadratic and linear exponential forms. In addition to these models, we also proposed the fitting of a logarithmic model to the data and the efficiency of the methodology was evaluated by Monte Carlo simulations, considering different scenarios for the parametric values. The isotonization of the data yielded an improvement in all the fitting quality parameters evaluated. Among the models used, the logarithmic presented estimates of the parameters more consistent with the values reported in literature.