changes_by: Change Scores from Numeric Data by Group
In quest: Prepare Questionnaire Data for Analysis

Description Usage Arguments Details Value See Also Examples

changes_by creates change scores (aka difference scores) from numeric data separately for each group. It is assumed that the data is already sorted within each group by time such that the first row for that group is earliest in time and the last row for that group is the latest in time.

1	changes_by(data, vrb.nm, grp.nm, n, undefined = NA, suffix)

`data`	data.frame of data.
`vrb.nm`	character vector of colnames from `data` specifying the variables.
`grp.nm`	character vector of colnames from `data` specifying the groups.
`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 `shifts_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 `shifts_by`.
`suffix`	character vector of length 1 specifying the string to append to the end of the colnames of the return object. The default depends on the `n` argument: 1) if `n` < 0, then `suffix` = `paste0("_hgw", -n)`, 2) if `n` > 0, then `suffix` = `paste0("_hdw", +n)`, 3) if `n` = 0, then `suffix` = "".

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

data.frame of change scores by group with colnames specified by paste0(vrb.nm, suffix).

change_by changes change shifts_by

changes_by(data = ChickWeight, vrb.nm = c("weight","Time"), grp.nm = "Chick", n = -1L)
changes_by(data = mtcars, vrb.nm = c("disp","mpg"), grp.nm = c("vs","am"), n = 1L)
changes_by(data = as.data.frame(CO2), vrb.nm = c("conc","uptake"),
   grp.nm = c("Type","Treatment"), n = 2L) # multiple grouping columns