Applied Statistical Methods - Notebook 9

Problem 1: Milk Dataset

Use the dataset milk from package pedigreemm and fit a sire model to each of the response variables (milk, fat, prot and scs) in the data. The dataset can be loaded using the command pedigreemm::milk. The other variables like lact and herd can be used as fixed effects. The sire column is used as a random effect. For this analysis, we assume that sires are unrelated.

Your Tasks

• Analyse the milk dataset from package pedigreemm using the function lme4::lmer() for all given response variables. You can use the same model for each of the responses.
• Compute the estimated heritability for each response variable, using the fact that the heritability \(h^2\) can be computed from the variance \(\sigma_s^2\) of the sire effects and the phenotypic variance \(\sigma_p^2\) with the formula

\[h^2 = \frac{4* \sigma_s^2}{\sigma_p^2} \]

• Compute the summary statistic using the function summary() of all the predicted sire breeding values. Solutions for the sire breeding values are obtained using the function ranef()

Your Solution

• Assign milk dataset to a tibble
• Analyse the data for each of the responses
• Compute estimated heritability
• Obtain summary statistics for predicted sire breeding values

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Latest Changes: 2022-05-06 07:35:37 (pvr)