Package index • modelbased

Model-based Estimations

describe_nonlinear() estimate_smooth(): Describe the smooth term (for GAMs) or non-linear predictors

estimate_contrasts(): Estimate Marginal Contrasts

estimate_expectation() estimate_link() estimate_prediction() estimate_relation(): Model-based predictions

estimate_grouplevel() reshape_grouplevel(): Group-specific parameters of mixed models random effects

estimate_means(): Estimate Marginal Means (Model-based average at each factor level)

estimate_slopes(): Estimate Marginal Effects

Data grids and Visualisation

visualisation_matrix(): Create a reference grid

visualisation_recipe(<estimate_predicted>) visualisation_recipe(<estimate_slopes>) visualisation_recipe(<estimate_grouplevel>): Automated plotting for 'modelbased' objects

Miscellaenous

describe_nonlinear() estimate_smooth(): Describe the smooth term (for GAMs) or non-linear predictors

get_emcontrasts() get_emmeans() get_emtrends() get_marginalcontrasts() get_marginalmeans() get_marginaltrends(): Consistent API for 'emmeans' and 'marginaleffects'

zero_crossings() find_inversions(): Find zero-crossings and inversion points

smoothing(): Smoothing a vector or a time series

Sample datasets

coffee_data: Sample dataset from a course about analysis of factorial designs

efc: Sample dataset from the EFC Survey

fish: Sample data set