To avoid a potentially wasteful complete cases analysis, it is common to impute the missing genotypes using a program such as MACH [Li et al., 2010], IMPUTE [Howie et al., 2009], or fastPHASE [Scheet and Stephens, 2006], and analyze the partly imputed data as if it were fully observed.
The key feature of the designs is that the probability that a unit is fully observed can depend on the value of the response, y.
We say the system is fully observed if Γ = {1,⋯, K}, and partially observed otherwise.
Note that the residual variance σ 0 2 = 1 unless the Gaussian phenotype is fully observed.
As Y is fully observed, an alternative to fitting model (1) is just to fit model (3) directly.
When the actual Gaussian response is fully observed, the threshold module is omitted from the model and the residual variance is estimated simultaneously to other model parameters.
Furthermore, if the model in Eq. (21) is fully observed, e.g., y1 = x1, y2 = x2, then all parameters in the model are identifiable.
Each value was given a value from 1 to 5 in a Likert-type scale, with verbal anchors located at each end (1: this value is completely ignored; 5: this value is fully observed).
(4) Conventional state- specific management, which involves the use of explicit objectives and models, is based on an assumption that objectives are appropriate, the resource system is fully observed, and projections of management impacts reflect full understanding.
