| debit_map_seq | R Documentation |
debit_map_seq() varies the reported means, standard
deviations, and sample sizes a few steps up and down and DEBIT-tests each
resulting value set. This shows whether a small error in reporting or
computing could explain an inconsistency.
Call audit() on the output for summary statistics.
debit_map_seq(
data,
digits_x,
digits_sd,
x = NULL,
sd = NULL,
n = NULL,
...,
data_type,
sd_meaning = c("sd_sample", "sd_pop", "sd_sample_or_pop", "se"),
formula = c("exact", "mean_n"),
rounding = "up_or_down",
threshold = 5,
symmetric = FALSE,
show_rec = FALSE,
var = c("x", "sd", "n"),
dispersion = 1:5,
out_min = "auto",
out_max = "auto",
include_reported = FALSE,
include_consistent = FALSE
)
data |
A data frame that |
digits_x, digits_sd |
Integer. The number of decimal places in |
x, sd, n |
Optionally, the names of the columns in |
... |
These dots must be empty. Every argument after them must be named in full. |
data_type |
String. As in |
formula, rounding, threshold, symmetric, sd_meaning |
Passed on to
|
show_rec |
Logical. If |
var |
String. The variables to disperse. Default is
|
dispersion |
Numeric. Steps up and down from the reported values, in
units of the last decimal place. Default is |
out_min, out_max |
Limits on the dispersed values. Both default to
|
include_reported |
Logical. Should the reported values themselves be
part of the sequences? Default is |
include_consistent |
Logical. Should consistent value sets be dispersed
as well, not just inconsistent ones? Default is |
A tibble with the columns of debit_map() output plus
diff_var, case, and var, as in grim_map_seq(). As there, the
other columns of data are dropped.
audit()audit() on debit_map_seq()
output returns a tibble with one row per case and these columns:
x, sd, and n: the reported values, with data_type and their
consistency.
hits_total: the number of DEBIT-consistent value sets found within the
dispersion range.
hits_x, hits_sd, hits_n: the number found by varying x, sd,
and n, respectively. If both include_reported and include_consistent
are TRUE, a consistent reported value set is counted as well: once per
variable here, and once in hits_total.
diff_x: the distance from x to the nearest consistent dispersed
value, in dispersion steps. diff_x_up and diff_x_down are the signed
steps to the nearest consistent value above and below (_down is
negative).
diff_sd, diff_sd_up, diff_sd_down: the same for sd.
diff_n, diff_n_up, diff_n_down: the same for n.
A count or distance is NA if it depends on a dispersed value set whose
consistency is NA, on a variable whose reported value is missing, which
is not dispersed, or on rows removed from the output, as by filter().
Call audit() again on that summary to summarize these columns further.
na_count and na_rate there count the cases without a consistent value
within the dispersion range, and those that a missing value leaves
unknown.
# `debit_map_seq()` takes the same input as `debit_map()`:
pigs3
out <- pigs3 |>
dplyr::slice(3:4) |>
debit_map_seq(digits_x = 2, digits_sd = 2, data_type = "integer")
out
# Case-wise summaries:
out |>
audit()
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