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Whilst linear mixed models offer a flexible approach to handle data with multiple sources of random variability, the related hypothesis testing for the fixed effects often encounters obstacles when the

Whilst linear mixed models offer a flexible approach to handle data with multiple sources of random variability, the related hypothesis testing for the fixed effects often encounters obstacles when the sample size is small and the underlying distribution for the test statistic is unknown. Consequently, five methods of denominator degrees of freedom approximations (residual, containment, between-within, Satterthwaite, Kenward-Roger) are developed to overcome this problem.

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Date Created
  • 2020
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  • Text
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    • Masters Thesis Statistics 2020

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