change_by: Change Scores from a Numeric Vector by Group
In quest: Prepare Questionnaire Data for Analysis

Description Usage Arguments Details Value See Also Examples

change_by creates a change score (aka difference score) from a numeric vector separately for each group. It is assumed that the vector is already sorted within each group by time such that the first element for that group is earliest in time and the last element for that group is the latest in time.

1	change_by(x, grp, n, undefined = NA)

`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.
`n`	integer vector with length 1. Specifies how the change score is calculated. If `n` is positive, then the change score is calculated from lead - original; if `n` is negative, then the change score is calculated from original - lag. The magnitude of `n` determines how many rows are shifted for the lead/lag within the calculation. See details of `shift_by`.
`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 details of `shift_by`.

It is recommended to use L when specifying n to prevent problems with floating point numbers. shift_by tries to circumvent this issue by a call to round within shift_by if n is not an integer; however that is not a complete fail safe. The problem is that as.integer(n) implicit in shift_by truncates rather than rounds. See details of shift_by.

an atomic vector of the same length as x that is the change score by group. If x and undefined are different typeofs, then the return will be coerced to the more complex typoof (i.e., complex to simple: character, double, integer, logical).

changes_by change changes shift_by

change_by(x = ChickWeight[["Time"]], grp = ChickWeight[["Chick"]], n = -1L)
tmp_nm <- c("vs","am") # multiple grouping vectors
change_by(x = mtcars[["disp"]], grp = mtcars[tmp_nm], n = +1L)
tmp_nm <- c("Type","Treatment") # multiple grouping vectors
change_by(x = as.data.frame(CO2)[["uptake"]], grp = as.data.frame(CO2)[tmp_nm], n = 2L)