Chapter 11 Linear Mixed-Effects Models
- Mixed-effects model
\(y = X\beta + Zu + e\)
- the elements of \(\beta\) are considered to be non-random and are called fixed effects.
- the elements of \(u\) are random variables and are called random effects.
- We assume that \(E(e) = 0, Var(e) = R, E(u) = 0, Var(u) = G, Cov(u, e) = 0\)
- \(E(y) = X\beta\), \(Var(y) = ZGZ' + R \equiv \Sigma\), \(E(y\mid u) = X\beta + Zu\)
When there are \(m\) random factors, we can partition \(Z\) and \(u\) as \(Z = [Z_1, \ldots, Z_m]\) and \(u = [u_1', \ldots, u_m']'\) so that \(Zu = \sum_{j = 1}^m Z_ju_j\).
- We often assume that all random effects are mutually independent and random effects associated with \(j\)th random factor have variance \(\sigma_j^2\). Then, \(Var(y) = ZGZ' + R = \sum_{j=1}^R \sigma_j^2 Z_jZ_j' + \sigma_e^2I\).
- The unknown variance parameters \(\sigma_j^2, \sigma_e^2\) are called variance components.
Experimental Design Terminology
- Experiment: An investigation in which the investigator applies some treatments to experimental units and then observes the effect of the treatments on the experimental units by measuring one or more response variables.
- Treatment: a condition or set of conditions applied to experimental units in an experiment.
- Experimental Unit: the physical entity to which a treatment is randomly assigned and independently applied.
- Response Variable: a characteristic of an experimental unit that is measured after treatment and analyzed to assess the effects of treatments on experimental units.
- Observational Unit: the unit on which a response variable is measured.
- Completely Randomized Design (CRD) – experimental design in which, for given number of experiment units per treatment, all possible assignments of treatments to experimental units are equally likely.
- Block – a group of experimental units that, prior to treatment, are expected to be more like one another (with respect to one or more response variables) than experimental units in general.
- Randomized Complete Block Design (RCBD) – experimental design in which separate and completely randomized treatment assignments are made for each of multiple blocks in such a way that all treatments have at least one experimental unit in each block.
Whenever an experiment involves multiple observations per experimental unit, it is important to include a random effect for each experimental unit.
Without a random effect for each experimental unit, a one-to-one correspondence between observations and experimental units is assumed.