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This article Xiaobian for you to introduce in detail "what is the concept of web measurement day model and random model", the content is detailed, the steps are clear, and the details are handled properly. I hope this article "what is the concept of web measurement day model and random model" can help you solve your doubts.

1. Concept distinction 1.1.The difference between measurement day model (Test-day-model) and random regression model (Random-regression-model)

The main purpose of the daily determination model is to analyze the models for different determination of daily milk production traits of dairy cows.

Random regression model mainly analyzes the data of an individual with multiple observations, that is, longitudinal data (longitudinal data) or panel data (panel data).

The daily measurement model is a type of stochastic model.

1.2 what data can be analyzed by random regression model in animal breeding?

Body weight, body length, etc., measured at different time points

Milk yield, feed consumption, fat composition changes, egg production and so on measured at different time points.

Litter size of different parity, etc.

two。 Analysis methods of Longitudinal data 2.1 characteristics of Longitudinal data Model

Consider the relationship between different observations of individuals, and each individual because of individual specificity, the relationship is different. These models add the differences of different individuals as random factors to the regression model to reflect the influence of individuals on their repeated measurements.

2.2 Common models for longitudinal data analysis

Random effect model

Variance component model

Multi-layer model

Multi-level model

Two-step model

Random effect mixed model

Random regression model

Hierarchical linear model

3. Advantage of Stochastic regression Model 3.1 difference between Stochastic regression Model and repetitive Force Model

In animal breeding, such as egg production, wool traits, litter size of pigs and so on, repeatability can be calculated because of repeated measurements.

Phenotype = mean + additive effect + repeatability effect + residual

The main reason why the repetitive force effect can be dissected is that it has repeated observation data, just as in the two-factor analysis of variance, only repeated observations at different levels of interaction can analyze the significance of the interaction.

3.2 the difference between random regression model and multi-character model

The multi-trait model is mainly because the traits are not independent. In this case, the multi-trait model can be used to estimate the variance and covariance components between traits and calculate the genetic correlation, which can be used for indirect selection in breeding. For example, the body weight of pigs for 50 days, 100 days and 150 days is related to each other. Using the multi-trait model, the genetic correlation among the three traits can be estimated and the purpose of early selection can be achieved.

When there are more traits, such as 10 traits, 45 parameters need to be estimated. For example, there are hundreds of traits in dairy cows on different test days (5-305 days), and more parameters need to be estimated, which can not be realized, so multi-trait model can not be used for analysis.

3.3 Analytical advantages of measuring daily regression model

1, you can analyze the situation of multiple traits, such as 100 days, 300 days milk yield

2. By using Legendre polynomial, comparing different orders and selecting the optimal model, the results can be transformed into the form of conventional multi-character model, including genetic correlation and phenotypic correlation, heritability, repeatability and so on.

3. Compared with the multi-character model, the model is easier to converge and the result is more accurate.

3.4 complexity from random regression model to animal model

4. The Analysis idea of measuring Day Model 4.1 the operation method of determining day regression model 1: writing model

4.2 Operation method for determining daily regression model 2: parameter estimation

4.3 Operation method of measuring daily regression model 3: result presentation

5. Literature Analysis: evaluation of genetic parameters of Holstein cows by determination Day Model 5.1 Literature title

5.2 data

Basic information of data

The data were divided into 10 months according to the DIM of the measurement day, which was mainly used for the definition of residual heterogeneity.

5.3 Model Writing

5.4 significance of fixed factor and blue value

5.5 screening the optimal model evaluation, the additive is 4th order, and the permanent environmental effect is 3rd order.

5.6 variation curve of variance components with time

5.7 variation curves of heritability and repeatability with time

5.9 genetic correlation and phenotypic correlation in different determination days

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