This method facilitates the interpretation of linear mixed-effects models and is a byproduct of the method fxInteractive.glm for generalized linear models.
● Data Source:
CranContrib
● Keywords:
● Alias: fxInteractive.lme
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This method facilitates the interpretation of multiple linear regression models and is a byproduct of the method fxInteractive.glm for generalized linear models.
● Data Source:
CranContrib
● Keywords:
● Alias: fxInteractive.lm
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Wrapper function to provide a variable name of type character to rp.slider.
● Data Source:
CranContrib
● Keywords: internal
● Alias: wrapRpSlider
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All levels of the factors from a data.frame provided are combined, each combination of factor levels is referred to as group.
● Data Source:
CranContrib
● Keywords:
● Alias: factorCombinations
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This method implements proposals for the interpretation of models for binary outcomes made by Hoetker (2007) but works for other types of generalized linear models as well. The method is also suitable for generalized additive models fitted with gam (package gam and mgcv).
● Data Source:
CranContrib
● Keywords:
● Alias: fxInteractive.glm
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The implementation is based on the package rpanel and provides an interactive visualization of effects, response functions and marginal effects for different kinds of regression models. Major features are the interactive approach and the handling of the effects of categorical covariates: if two or more factors are used as covariates every combination of the levels of each factor (referred to as groups) is treated separately. The automatic calculation of marginal effects and a number of possibilities to customize the graphical output are useful features as well. In the accompanying vignette the usage is described in detail. Please refer to the documentation of the generic function fxInteractive for available methods.
● Data Source:
CranContrib
● Keywords: package
● Alias: LinRegInteractive, LinRegInteractive-package
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fxInteractive is a generic function for the interactive visualization of the results of various types of regression models. Originally the function was developed to translate proposals for the interpretation of models for binary outcomes made by Hoetker (2007) into practice. The function invokes particular methods for different kinds of fitted-model objects, see the list of available methods in the details. The implementation is based on the package rpanel. Major features are the interactive approach and the handling of the effects of categorical covariates: if two or more factors are used as covariates every combination of the levels of each factor (referred to as groups) is treated separately. The automatic calculation of marginal effects and a number of possibilities to customize the graphical output are useful features as well. In the accompanying vignette the usage is described in detail.
● Data Source:
CranContrib
● Keywords:
● Alias: fxInteractive
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providing 
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