LAPOP Grouped Bar Graph Pre-Processing

This function creates dataframes which can then be input in lapop_ccm for comparing values for multiple variables across countries with a bar graph using LAPOP formatting.

Usage

lpr_ccm(
  data,
  outcome_vars,
  xvar = "pais_lab",
  rec1 = c(1, 1),
  rec2 = c(1, 1),
  rec3 = c(1, 1),
  ci_level = 0.95,
  mean = FALSE,
  filesave = "",
  cfmt = "",
  sort = "y",
  order = "hi-lo",
  ttest = FALSE,
  keep_nr = FALSE
)

Arguments

data: A survey object. The data that should be analyzed.
outcome_vars: Character vector. Outcome variable(s) of interest to be plotted across country (or other x variable). Max of 3 (three) variables.
xvar: Character string. Outcome variables are broken down by this variable. You can set xvar to "wave" or "year" for cross-time comparisons. Default: pais_lab.
rec1, rec2, rec3: Numeric. The minimum and maximum values of the outcome variable that should be included in the numerator of the percentage. For example, if the variable is on a 1-7 scale and rec1 is c(5, 7), the function will show the percentage who chose an answer of 5, 6, 7 out of all valid answers. Can also supply one value only, to produce the percentage that chose that value out of all other values. Default: c(1, 1).
ci_level: Numeric. Confidence interval level for estimates. Default: 0.95
mean: Logical. If TRUE, will produce the mean of the variable rather than rescaling to percentage. Default: FALSE.
filesave: Character. Path and file name to save the dataframe as csv.
cfmt: Character. Changes the format of the numbers displayed above the bars. Uses sprintf string formatting syntax. Default is whole numbers for percentages and tenths place for means.
sort: Character. On what value the bars are sorted. Options are "y" (default; for the value of the first outcome variable), "xv" (for the underlying values of the x variable), "xl" (for the labels of the x variable, i.e., alphabetical).
order: Character. How the bars should be sorted. Options are "hi-lo" (default) or "lo-hi".
ttest: Logical. If TRUE, will conduct pairwise t-tests for difference of means between all outcomes vs. all x-vars and save them in attr(x, "t_test_results"). Default: FALSE.
keep_nr: Logical. If TRUE, will convert "don't know" (missing code .a) and "no response" (missing code .b) into valid data (value = 99) and use them in the denominator when calculating percentages. The default is to examine valid responses only. Default: FALSE.

Value

Returns a data frame, with data formatted for visualization by lapop_ccm()

Author

Luke Plutowski, luke.plutowski@vanderbilt.edu && Robert Vidigal, robert.vidigal@vanderbilt.edu

Examples


if (FALSE) { # \dontrun{
# Multiple outcomes
lpr_ccm(gm23,
outcome_vars = c("vic1ext", "aoj11"),
rec1 = c(1, 1),
rec2 = c(3, 4),
ttest = TRUE)} # }

if (FALSE) { # \dontrun{
# Multiple outcomes over years
lpr_ccm(gm23,
outcome_vars = c("vic1ext", "aoj11"),
xvar = "wave",
rec1 = c(1, 1),
rec2 = c(3, 4),
ttest = TRUE)} # }