Estimation of Model-Based Predictions, Contrasts and Means


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Documentation for package ‘modelbased’ version 0.11.2

Help Pages

coffee_data Sample dataset from a course about analysis of factorial designs
describe_nonlinear Describe the smooth term (for GAMs) or non-linear predictors
describe_nonlinear.data.frame Describe the smooth term (for GAMs) or non-linear predictors
efc Sample dataset from the EFC Survey
estimate_contrasts Estimate Marginal Contrasts
estimate_contrasts.default Estimate Marginal Contrasts
estimate_expectation Model-based predictions
estimate_grouplevel Group-specific parameters of mixed models random effects
estimate_grouplevel.brmsfit Group-specific parameters of mixed models random effects
estimate_grouplevel.default Group-specific parameters of mixed models random effects
estimate_link Model-based predictions
estimate_means Estimate Marginal Means (Model-based average at each factor level)
estimate_prediction Model-based predictions
estimate_relation Model-based predictions
estimate_slopes Estimate Marginal Effects
estimate_smooth Describe the smooth term (for GAMs) or non-linear predictors
find_inversions Find zero-crossings and inversion points
fish Sample data set
get_emcontrasts Consistent API for 'emmeans' and 'marginaleffects'
get_emmeans Consistent API for 'emmeans' and 'marginaleffects'
get_emtrends Consistent API for 'emmeans' and 'marginaleffects'
get_marginalcontrasts Consistent API for 'emmeans' and 'marginaleffects'
get_marginalmeans Consistent API for 'emmeans' and 'marginaleffects'
get_marginaltrends Consistent API for 'emmeans' and 'marginaleffects'
modelbased-options Global options from the modelbased package
plot.estimate_means Automated plotting for 'modelbased' objects
plot.estimate_predicted Automated plotting for 'modelbased' objects
pool_contrasts Pool contrasts and comparisons from 'estimate_contrasts()'
pool_predictions Pool Predictions and Estimated Marginal Means
pool_slopes Pool Predictions and Estimated Marginal Means
print.estimate_contrasts Printing modelbased-objects
puppy_love More puppy therapy data
reshape_grouplevel Group-specific parameters of mixed models random effects
reshape_grouplevel.estimate_grouplevel Group-specific parameters of mixed models random effects
smoothing Smoothing a vector or a time series
visualisation_recipe.estimate_grouplevel Automated plotting for 'modelbased' objects
visualisation_recipe.estimate_predicted Automated plotting for 'modelbased' objects
visualisation_recipe.estimate_slopes Automated plotting for 'modelbased' objects
zero_crossings Find zero-crossings and inversion points