LAPOP Dumbbell Graphs — lpr

This function creates dataframes which can then be input in lapop_dumb for comparing means of a variable across countries and two waves using LAPOP formatting.

Usage

lpr_dumb(
  data,
  outcome,
  xvar = "pais",
  over,
  rec = c(1, 1),
  ci_level = 0.95,
  mean = FALSE,
  filesave = "",
  cfmt = "",
  sort = "prop2",
  order = "hi-lo",
  ttest = FALSE,
  keep_nr = FALSE
)

Arguments

data: A survey object. The data that should be analyzed.
outcome: Outcome variable(s) of interest to be plotted across countries and waves, supplied as a character string or vector of strings.
xvar: Character. The grouping variable to be plotted along the x-axis (technically, the vertical axis for lapop_dumb). Usually country (pais). Default: "pais".
over: Numeric. A vector of values for "wave" that specify which two waves should be included in the plot.
rec: 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 rec 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 recoding 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 "prop1" (for the value of the outcome variable in wave 1), "prop2" (default; for the value of the outcome variable in wave 2), "xv" (for the underlying values of the x variable), "xl" (for the labels of the x variable, i.e., alphabetical), and "diff" (for the difference between the outcome between the two waves).
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 pais-wave combinations 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_dumb()

Author

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

Examples


require(lapop); data(cm23)

# Set Survey Context
cm23lpr <- lpr_data(cm23)

# Single outcome over years
lpr_dumb(cm23lpr,
outcome = "ing4",
rec = c(5, 7),
over = c("2018/19", "2023"),
sort = "diff")
#>     pais   wave1   prop1      lb1      ub1 proplabel1 wave2   prop2      lb2
#> 1 Brasil 2018/19 59.9975 56.91498 63.08002        60%  2023 63.8175 60.94615
#>        ub2 proplabel2     diff
#> 1 66.68884        64% 3.819996

# Multiple outcomes over years
lpr_dumb(cm23lpr,
outcome=c("b13","b21", "b31"),
rec=c(5,7),
over=c("2018/19", "2023"))
#>   pais   wave1    prop1 proplabel1 wave2    prop2 proplabel2      lb1      ub1
#> 1  b31 2018/19 43.08618        43%  2023 42.16415        42% 40.06770 46.10465
#> 2  b13 2018/19 30.32138        30%  2023 35.25472        35% 27.76127 32.88150
#> 3  b21 2018/19 13.61917        14%  2023 20.52433        21% 11.52554 15.71279
#>        lb2      ub2
#> 1 38.97057 45.35774
#> 2 32.18235 38.32709
#> 3 17.82247 23.22619