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.
Arguments
- x
A numeric vector.
- values
Character vector, naming a pattern for which representative values should be calculcated.
"minmax":
(default) minimum and maximum values (lower and upper bounds) of the moderator are used to plot the interaction between independent variable and moderator."meansd"
: 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."zeromax"
: 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."fivenum":
calculates and uses the Tukey's five number summary (minimum, lower-hinge, median, upper-hinge, maximum) of the moderator value."quart"
: calculates and uses the quartiles (lower, median and upper) of the moderator value, including minimum and maximum value."quart2"
: calculates and uses the quartiles (lower, median and upper) of the moderator value, excluding minimum and maximum value."terciles"
: calculates and uses the terciles (lower and upper third) of the moderator value, including minimum and maximum value."terciles2"
: calculates and uses the terciles (lower and upper third) of the moderator value, excluding minimum and maximum value."all"
: uses all values of the moderator variable. Note that this option only applies totype = "eff"
, for numeric moderator values.
Value
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.
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