Graphical and tabular effect displays, e.g., of interactions, for various statistical models with linear predictors.

John Fox, Sanford Weisberg, Brad Price, Michael Friendly, Jangman Hong, Robert Anderson, David Firth, Steve Taylor, and the R Core Team.

Maintainer: John Fox <jfox@mcmaster.ca>

Package: | effects |

Version: | 4.2-2 |

Date: | 2022-02-16 |

Depends: | R (>= 3.5.0), carData |

Suggests: | pbkrtest (>= 0.4-4), nlme, MASS, poLCA, heplots, splines, ordinal, car, knitr, betareg, alr4, robustlmm |

Imports: | lme4, nnet, lattice, grid, colorspace, graphics, grDevices, stats, survey, utils, estimability, insight |

LazyLoad: | yes |

License: | GPL (>= 2) |

URL: | https://www.r-project.org, https://socialsciences.mcmaster.ca/jfox/ |

This package creates effect displays for various kinds of models, as partly explained in the references.
Typical usage is `plot(allEffects(model))`

or `plot(predictorEffects(model))`

,
where `model`

is an appropriate fitted-model object.
Additional arguments to `allEffects`

, `predictorEffects`

and `plot`

can be used to customize the resulting
displays. The function `effect`

can be employed to produce an effect display for a
particular term in the model, or to which terms in the model are marginal. The function `predictorEffect`

can be used
to construct an effect display for a particularly predictor. The function `Effect`

may similarly be used to produce an effect display for any combination of predictors. In any of the cases, use `plot`

to graph the resulting effect object. For linear and generalized linear models it is also possible to plot
partial residuals to obtain (multidimensional) component+residual plots.
See `?effect`

, `?Effect`

, `?predictorEffect`

, and `?plot.eff`

for details.

Fox, J. and S. Weisberg (2019)
*An R Companion to Applied Regression, Third Edition*
Sage Publications.

Fox, J. (1987)
Effect displays for generalized linear models.
*Sociological Methodology*
**17**, 347--361.

Fox, J. (2003)
Effect displays in R for generalised linear models.
*Journal of Statistical Software*
**8:15**, 1--27, tools:::Rd_expr_doi("10.18637/jss.v008.i15").

Fox, J. and R. Andersen (2006)
Effect displays for multinomial and proportional-odds logit models.
*Sociological Methodology*
**36**, 225--255.

Fox, J. and J. Hong (2009).
Effect displays in R for multinomial and proportional-odds logit models:
Extensions to the effects package.
*Journal of Statistical Software*
**32:1**, 1--24, tools:::Rd_expr_doi("10.18637/jss.v032.i01").

Fox, J. and S. Weisberg (2018).
Visualizing Fit and Lack of Fit in Complex Regression Models:
Effect Plots with Partial Residuals.
*Journal of Statistical Software*
**87:9**, 1--27, tools:::Rd_expr_doi("10.18637/jss.v087.i09").