decomposes: Decompose Numeric Data by Group
In quest: Prepare Questionnaire Data for Analysis

Description Usage Arguments Value See Also Examples

decomposes decomposes numeric data by group 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-group components.

decomposes(
  data,
  vrb.nm,
  grp.nm,
  grand = TRUE,
  n.shift = NULL,
  undefined = NA,
  suffix.wth = "_w",
  suffix.btw = "_b",
  suffix.grand = "c",
  suffix.lead = "_dw",
  suffix.lag = "_gw"
)

`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.
`grand`	logical vector of length 1 specifying whether grand-mean centered versions of the the between-group components 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_by` details.
`undefined`	atomic vector of length 1 (probably makes sense to be the same typeof as the vectors in `data[vrb.nm]`). Specifies what to insert for undefined values after the shifting takes place. See details of `Shift_by`.
`suffix.wth`	character vector with a single element specifying the string to append to the end of the within-group component colnames of the return object.
`suffix.btw`	character vector with a single element specifying the string to append to the end of the between-group component colnames of the return object.
`suffix.grand`	character vector with a single element specifying the string to append to the end of the grand-mean centered version of the between-group component colnames of the return object. Note, this is a string that is appended after `suffix.btw` has already been appended.
`suffix.lead`	character vector with a single element specifying the string to append to the end of the positive shift colnames of the return object. Note, `decomposes` will add `abs(n.shift)` to the end of `suffix.lead`.
`suffix.lag`	character vector with a single element specifying the string to append to the end of the negative shift colnames of the return object. Note, `decomposes` will add `abs(n.shift)` to the end of `suffix.lag`.

data.frame with nrow = nrow(data and rownames = row.names(data). The first set of columns correspond to the within-group components, followed by the between-group components. If grand = TRUE, then the next set of columns correspond to the grand-mean centered between-group components. If shift != NULL, then the last columns are the shifts by group indicated by n.shift, where the shifts of data[vrb.nm] are first and then the shifts of the within-group components are second.

decompose centers_by aggs shifts_by

ChickWeight2 <- as.data.frame(ChickWeight)
row.names(ChickWeight2) <- as.numeric(row.names(ChickWeight)) / 1000
decomposes(data = ChickWeight2, vrb.nm = c("weight","Time"), grp.nm = "Chick")
decomposes(data = ChickWeight2, vrb.nm = c("weight","Time"), grp.nm = "Chick",
   suffix.wth = ".wth", suffix.btw = ".btw", suffix.grand = ".grand")
decomposes(data = as.data.frame(CO2), vrb.nm = c("conc","uptake"),
   grp.nm = c("Type","Treatment")) # multiple grouping columns
decomposes(data = as.data.frame(CO2), vrb.nm = c("conc","uptake"),
   grp.nm = c("Type","Treatment"), n.shift = 1) # with lead
decomposes(data = as.data.frame(CO2), vrb.nm = c("conc","uptake"), grp.nm = c("Type","Treatment"),
   n.shift = c(+2, +1, -1, -2)) # with multiple lead/lags