1 Cut zucchini in half lengthwise (if needed, trim bottom so it sits still in baking dish) 2  Scoop out the center where the seeds are with a spoon.  Mix the crushed garlic, olive oil, salt and pepper in a small bowl. Brush surface of zucchini with the mixture.
In econometrics, random effects models are used in the analysis of hierarchical or panel data when one assumes no fixed effects (it allows for individual effects). The random effects model is a special case of the fixed effects model.here are two common assumptions made about the individual specific effect, the random effects assumption and the fixed effects assumption. The random effects assumption (made in a random effects model) is that the individual specific effects are uncorrelated with the independent variables.
For nominal data, if the response is a binary variable (that is only two possible values such as graduate in four years or not), then, use Logistic regression model. If the response has more than two categories, use multinomial logistic regression. For ordinal data, if the response follows Poisson distribution, use Poisson regression model. In general, one can use log-linear models for ordinal data. In many applications, the relationship between response variable and predictors are not linear, but may be linearized. Generalized linear modeling techniques are useful.