Transform data in growthcleanr format into wide structure for BMI calculation

longwide transforms data from long to wide format. Ideal for transforming output from growthcleanr::cleangrowth() into a format suitable for growthcleanr::ext_bmiz().

longwide(
  long_df,
  id = "id",
  subjid = "subjid",
  sex = "sex",
  agedays = "agedays",
  param = "param",
  measurement = "measurement",
  gcr_result = "gcr_result",
  include_all = FALSE,
  inclusion_types = c("Include"),
  extra_cols = NULL,
  keep_unmatched_data = FALSE
)

Arguments

long_df: A data frame to be transformed. Expects columns: id, subjid, sex, agedays, param, measurement, and gcr_result.
id: name of observation ID column
subjid: name of subject ID column
sex: name of sex descriptor column
agedays: name of age (in days) descriptor column
param: name of parameter column to identify each type of measurement
measurement: name of measurement column containing the actual measurement data
gcr_result: name of column of results from growthcleanr::cleangrowth()
include_all: Determines whether the function keeps all exclusion codes. If TRUE, all exclusion types are kept and the inclusion_types argument is ignored. Defaults to FALSE.
inclusion_types: Vector indicating which exclusion codes from the cleaning algorithm should be included in the data, given that include_all is FALSE. For all options, see growthcleanr::cleangrowth(). Defaults to c("Include").
extra_cols: Vector of additional columns to include in the output. If a column C1 differs on agedays matched height and weight values, then include separate ht_C1 and wt_C1 columns as well as a match_C1 column that gives booleans indicating where ht_C1 and wt_C1 are the same. If the agedays matched height and weight columns are identical, then only include a single version of C1. Defaults to empty vector (not keeping any additional columns).
keep_unmatched_data: boolean indicating whether to keep height/weight observations that do not have a matching weight/height on that day

Value

Returns a data frame transformed from long to wide. Includes only values flagged with indicated inclusion types. Potentially includes additional columns if arguments are passed to extra_cols. For each subject, heights without corresponding weights for a given age (and vice versa) will be dropped unless keep_unmatched_data is set to TRUE.

Examples

# Run on a small subset of given data
df <- as.data.frame(syngrowth)
df <- df[df$subjid %in% unique(df[, "subjid"])[1:2], ]
df <- cbind(df,
            "gcr_result" = cleangrowth(df$subjid,
                                       df$param,
                                       df$agedays,
                                       df$sex,
                                       df$measurement))
# Convert to wide format
wide_df <- longwide(df)

# Include all inclusion types
wide_df <- longwide(df, include_all = TRUE)

# Specify all inclusion codes
wide_df <- longwide(df, inclusion_types = c("Include", "Exclude-Carried-Forward"))