long2wide: Reshape Multiple Scores From Long to Wide

In quest: Prepare Questionnaire Data for Analysis

Description

long2wide reshapes data from long to wide. This if often necessary to do with multilevel data where variables in the long format seek to be reshaped to multiple sets of variables in the wide format. If only one column needs to be reshaped, then you can use unstack2 or cast - but that does not work for *multiple* columns.

Usage

long2wide(
  data,
  vrb.nm,
  grp.nm,
  obs.nm,
  sep = ".",
  colnames.by.obs = TRUE,
  keep.attr = FALSE
)

Arguments

data	data.frame of data.
vrb.nm	character vector of colnames from data specifying the variables to be reshaped. In longitudinal panel data, this would be the scores.
grp.nm	character vector of colnames from data specifying the groups. In longitudnal panel data, this would be the participant ID variable.
obs.nm	character vector of length 1 with a colname from data specifying the observation within each group. In longitudinal panel data, this would be the time variable.
sep	character vector of length 1 specifying the string that separates the name prefix (e.g., score) from it's number suffix (e.g., timepoint). If sep = "", then that implies there is no string separating the name prefix and the number suffix (e.g., "outcome1").
colnames.by.obs	logical vector of length 1 specifying whether to sort the return object colnames by the observation label (TRUE) or by the order of vrb.nm. See the example at the end of the "MULTIPLE GROUPING VARIABLES" section of the examples.
keep.attr	logical vector of length 1 specifying whether to keep the "reshapeWide" attribute (from reshape) in the return object.

Details

long2wide uses reshape(direction = "wide") to reshape the data. It attempts to streamline the task of reshaping long to wide as the reshape arguments can be confusing because the same arguments are used for wide vs. long reshaping. See reshape if you are curious.

Value

data.frame with nrow equal to nrow(unique(data[grp.nm])) and number of reshaped columns equal to length(vrb.nm) * unique(data[[obs.nm]]). The colnames will have the structure paste0(vrb.nm, sep, unique(data[[obs.nm]])). The reshaped colnames are sorted by the observation labels if colnames.by.obs = TRUE and sorted by vrb.nm if colnames.by.obs = FALSE. Overall, the columns are in the following order: 1) grp.nm of the groups, 2) reshaped columns, 3) additional columns that were not reshaped.

See Also

wide2long reshape unstack2

Examples

# SINGLE GROUPING VARIABLE
dat_long <- as.data.frame(ChickWeight) # b/c groupedData class does weird things...
w1 <- long2wide(data = dat_long, vrb.nm = "weight", grp.nm = "Chick",
   obs.nm = "Time") # NAs inserted for missing observations in some groups
w2 <- long2wide(data = dat_long, vrb.nm = "weight", grp.nm = "Chick",
   obs.nm = "Time", sep = "_")
head(w1); head(w2)
w3 <- long2wide(data = dat_long, vrb.nm = "weight", grp.nm = "Chick",
   obs.nm = "Time", sep = "_T", keep.attr = TRUE)
attributes(w3)

# MULTIPLE GROUPING VARIABLE
tmp <- psychTools::sai
grps <- interaction(tmp[1:3], drop = TRUE)
dups <- duplicated(grps)
dat_long <- tmp[!(dups), ] # for some reason there are duplicate groups in the data
vrb_nm <- str2str::pick(names(dat_long), val = c("study","time","id"), not = TRUE)
w4 <- long2wide(data = dat_long, vrb.nm = vrb_nm, grp.nm = c("study","id"),
   obs.nm = "time")
w5 <- long2wide(data = dat_long, vrb.nm = vrb_nm, grp.nm = c("study","id"),
   obs.nm = "time", colnames.by.obs = FALSE) # colnames sorted by `vrb.nm` instead
head(w4); head(w5)

quest documentation built on Sept. 10, 2021, 5:07 p.m.