LMM: Random factors

5 important questions on LMM: Random factors

What does a randomized block design look like?

  • Take out the variation that can be explained by the river (SSriver)
  • add block as random factor
  • N-application is carried out on 'SStotal-SSriver'
  • remaining analysis is more sensitive to N-appl
  • Mixed model: fixed and random factors/effects

What is a latin square design?

A LMM with 2 random factors and one fixed factor.

What are solutions for pseudoreplication?

  1. Independent samplig
  2. work with the means
  3. (G)LMM + random factor
  4. Repeated measurs
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What is the main difference between the randomized block design and the latin square?

In a randomized block design you can control for the effect of one environmental gradient, whereas a Latin square design permits you to control for the influence of two environmental gradients.

Why is a G(z)LMM prefered over a paired t-test (when you have paired data)?

The paired t-test cannot include additional fixed factors, covariates or random effects.
  • the possibilities to use different data distributions,
  • the relative insensitivity to deviations from normality
  • the possibility to have variances that are dissimilar
  • you can analyse incomplete designs
  • you can include one or more random factors
  • you can better analyse datasets with missing data
  • you can accommodate a repeated structure in your dataset

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