| center {mlmtools} | R Documentation |
Centers variables for mixed effects models
Description
Centers variables using the group-mean (person-mean) centering approach for mixed-effects models, and adds these variables to the data frame.
Usage
center(
dataset,
x,
grouping,
type = "mean",
standardize = FALSE,
centerResult = FALSE
)
Arguments
dataset |
A dataset containing the variables to be centered and the grouping variable |
x |
The variable or variables to be centered |
grouping |
The variable or variables that define the grouping structure of the data |
type |
a function to compute the grouping summary variable |
standardize |
a logical value indicating whether x should be standardized before the computaion proceeds |
centerResult |
a logical value indicating whether resulting grouping summary variable values should be centered at 0 |
Value
Creates two new variables in the data frame - a mean of the desired variable computed for each unique value in the grouping variable and a deviation score for each observation within the grouping variable that is that observation's raw score subtracted from the group mean.
References
Enders, C. & Tofighi, D. (2007). Centering predictor variables in cross-sectional multilevel models: A new look at an old problem. Psychological Methods, 12(2), 121–138
Examples
data(instruction)
#Center student level socioeconomic status, "ses", around class mean "ses"
### To repress output: use invisible()
center(dataset = instruction, x = "ses", grouping = "classid")
#Center class-level variable teacher's mathematic prepartion,
# mathprep, around school mean "mathprep"
center(dataset = instruction, x = "mathprep", grouping = "schoolid")