Fixed Coefficients (generalized linear mixed models)
This view displays the value of each fixed coefficient in the model. Note that factors (categorical predictors) are indicator-coded within the model, so that effects containing factors will generally have multiple associated coefficients; one for each category except the category corresponding to the redundant coefficient.
Styles. There are different display styles, which are accessible from the Style dropdown list.
- Diagram. This is a chart which displays the intercept first, and then sorts effects from top to bottom in the order in which they were specified on the Fixed Effects settings. Within effects containing factors, coefficients are sorted by ascending order of data values. Connecting lines in the diagram are colored and weighted based on coefficient significance, with greater line width corresponding to more significant coefficients (smaller p-values). This is the default style.
- Table. This shows the values, significance tests, and confidence intervals for the individual model coefficients. After the intercept, the effects are sorted from top to bottom in the order in which they were specified on the Fixed Effects settings. Within effects containing factors, coefficients are sorted by ascending order of data values.
Multinomial. If the multinomial distribution is in effect, then the Multinomial drop-down list controls which target category to display. The sort order of the values in the list is determined by the specification on the Build Options settings.
Exponential. This displays exponential coefficient estimates and confidence intervals for certain model types, including Binary logistic regression (binomial distribution and logit link), Nominal logistic regression (multinomial distribution and logit link), Negative binomial regression (negative binomial distribution and log link), and Log-linear model (Poisson distribution and log link).
Significance. There is a Significance slider that controls which coefficients are shown in the view. Coefficients with significance values greater than the slider value are hidden. This does not change the model, but simply allows you to focus on the most important coefficients. By default the value is 1.00, so that no coefficients are filtered based on significance.