decompose {quest}

Decompose a Numeric Vector by Group

Description

decompose decomposes a numeric vector into within-group and between-group components via within-group centering and group-mean aggregation. There is an option to create a grand-mean centered version of the between-person component as well as lead/lag versions of the original vector and the within-group component.

Usage

decompose(x, grp, grand = TRUE, n.shift = NULL, undefined = NA)

Arguments

x

numeric vector.

grp

list of atomic vector(s) and/or factor(s) (e.g., data.frame), which each have same length as x. It can also be an atomic vector or factor, which will then be made the first element of a list internally.

grand

logical vector of length 1 specifying whether a grand-mean centered version of the the between-group component should be computed.

n.shift

integer vector specifying the direction and magnitude of the shifts. For example a one-lead is +1 and a two-lag is -2. See shift details.

undefined

atomic vector with length 1 (probably makes sense to be the same typeof as x). Specifies what to insert for undefined values after the shifting takes place. See shift details.

Value

data.frame with nrow = length(x) and row.names = names(x). The first two columns correspond to the within-group component (i.e., "wth") and the between-group component (i.e., "btw"). If grand = TRUE, then the third column corresponds to the grand-mean centered between-group component (i.e., "btw_c"). If shift != NULL, then the last columns are the shifts indicated by n.shift, where the shifts of x are first (i.e., "tot") and then the shifts of the within-group component are second (i.e., "wth"). The naming of the shifted columns is based on the default behavior of Shift_by. See the details of Shift_by. If you don't like the default naming, then call Decompose instead and use the different suffix arguments.

See Also

decomposes center_by agg shift_by

Examples

# single grouping variable
chick_data <- as.data.frame(ChickWeight) # because the "groupedData" class
   # calls `[.groupedData`, which is different than `[.data.frame`
decompose(x = ChickWeight[["weight"]], grp = ChickWeight[["Chick"]])
decompose(x = ChickWeight[["weight"]], grp = ChickWeight[["Chick"]],
   grand = FALSE) # no grand-mean centering
decompose(x = setNames(obj = ChickWeight[["weight"]],
   nm = paste0(row.names(ChickWeight),"_row")), grp = ChickWeight[["Chick"]]) # with names

# multiple grouping variables
tmp_nm <- c("Type","Treatment") # b/c Roxygen2 doesn't like c() in a []
decompose(x = as.data.frame(CO2)[["uptake"]], grp = as.data.frame(CO2)[tmp_nm])
decompose(x = as.data.frame(CO2)[["uptake"]], grp = as.data.frame(CO2)[tmp_nm],
   n.shift = 1)
decompose(x = as.data.frame(CO2)[["uptake"]], grp = as.data.frame(CO2)[tmp_nm],
   n.shift = c(+2, +1, -1, -2))