This function calculates representative values of a vector, like minimum/maximum values or lower, median and upper quartile etc., which can be used for numeric vectors to plot marginal effects at these representative values.

values_at(x, values = "meansd")

representative_values(x, values = "meansd")



A numeric vector.


Character vector, naming a pattern for which representative values should be calculcated.


(default) minimum and maximum values (lower and upper bounds) of the moderator are used to plot the interaction between independent variable and moderator.


uses the mean value of the moderator as well as one standard deviation below and above mean value to plot the effect of the moderator on the independent variable.


is similar to the "minmax" option, however, 0 is always used as minimum value for the moderator. This may be useful for predictors that don't have an empirical zero-value, but absence of moderation should be simulated by using 0 as minimum.


calculates and uses the quartiles (lower, median and upper) of the moderator value, including minimum and maximum value.


calculates and uses the quartiles (lower, median and upper) of the moderator value, excluding minimum and maximum value.


uses all values of the moderator variable. Note that this option only applies to type = "eff", for numeric moderator values.


A numeric vector of length two or three, representing the required values from x, like minimum/maximum value or mean and +/- 1 SD. If x is missing, a function, pre-programmed with n and length is returned. See examples.


data(efc) values_at(efc$c12hour)
#> [1] -8.4 42.4 93.2
values_at(efc$c12hour, "quart2")
#> [1] 10.0 20.0 42.8
mean_sd <- values_at(values = "meansd") mean_sd(efc$c12hour)
#> [1] -8.4 42.4 93.2