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Mixed linear models were constructed for each of the SF-36 summary scores.
Conventional repeated measurement analyses of variance, or mixed linear models in the case of unbalanced data, generally demonstrate a statistically significant advantage of active compounds over placebo after three weeks of treatment.
Bihourly behavioral differences from baseline values over the 14 d before calving were also evaluated using mixed linear models.
The restricted maximum likelihood (REML) procedure is useful for inferences about variance components in mixed linear models.
Analyses will include mixed linear models, ANCOVA, MANOVA procedures and logistic regression with generalized estimating equations.
Mixed linear models were used to estimate variance components for reliability assessment; dependability coefficients were used to simulate alternative test scenarios.
Each effect was adjusted for relevant covariates using mixed linear models.
All data analyses were performed using mixed linear models with variance components estimated by residual maximum likelihood [17].
Mixed linear models were fitted to the data using ASREML [26] to estimate variance components for the hip score (H).
Statistical analyses of the data had the objectives of fitting mixed linear models using ASREML [12] to estimate the genetic parameters of the nine traits.
In several association studies information about population structure and/or kinship has been included into the general linear regression and mixed linear models [6], [10], [12], [18].
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