ggeffects: new_data – R documentation

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new_data

Create a data frame from all combinations of predictor values

Description

Create a data frame for the "newdata"-argument that contains all combinations of values from the terms in questions. Similar to expand.grid(). The terms-argument accepts all shortcuts for representative values as in ggpredict().

Usage

new_data(model, terms, typical = "mean", condition = NULL)

data_grid(model, terms, typical = "mean", condition = NULL)

Arguments

`model`	A fitted model object.
`terms`	Character vector with the names of those terms from `model` for which all combinations of values should be created.
`typical`	Character vector, naming the function to be applied to the covariates over which the effect is "averaged". The default is "mean". See `?sjmisc::typical_value` for options.
`condition`	Named character vector, which indicates covariates that should be held constant at specific values. Unlike `typical`, which applies a function to the covariates to determine the value that is used to hold these covariates constant, `condition` can be used to define exact values, for instance `condition = c(covariate1 = 20, covariate2 = 5)`. See 'Examples'.

Value

A data frame containing one row for each combination of values of the supplied variables.

Examples

data(efc)
fit <- lm(barthtot ~ c12hour + neg_c_7 + c161sex + c172code, data = efc)
new_data(fit, c("c12hour [meansd]", "c161sex"))

nd <- new_data(fit, c("c12hour [meansd]", "c161sex"))
pr <- predict(fit, type = "response", newdata = nd)
nd$predicted <- pr
nd

# compare to
ggpredict(fit, c("c12hour [meansd]", "c161sex"))

ggeffects

Create Tidy Data Frames of Marginal Effects for 'ggplot' from Model Outputs

v1.1.0

GPL-3

Authors

Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>), Frederik Aust [ctb] (<https://orcid.org/0000-0003-4900-788X>), Sam Crawley [ctb] (<https://orcid.org/0000-0002-7847-0411>), Mattan S. Ben-Shachar [ctb] (<https://orcid.org/0000-0002-4287-4801>)

Initial release