debit_map_total_n | R Documentation |
debit_map_total_n()
extends DEBIT to cases where only group
means and standard deviations (SDs) were reported, not group sizes.
The function is analogous to grim_map_total_n()
and
grimmer_map_total_n()
, relying on the same infrastructure.
debit_map_total_n(
data,
x1 = NULL,
x2 = NULL,
sd1 = NULL,
sd2 = NULL,
dispersion = 0:5,
n_min = 1L,
n_max = NULL,
constant = NULL,
constant_index = NULL,
...
)
data |
Data frame with string columns |
x1 , x2 , sd1 , sd2 |
Optionally, specify these arguments as column names in
|
dispersion |
Numeric. Steps up and down from half the |
n_min |
Numeric. Minimal group size. Default is 1. |
n_max |
Numeric. Maximal group size. Default is |
constant |
Optionally, add a length-2 vector or a list of length-2
vectors (such as a data frame with exactly two rows) to accompany the pairs
of dispersed values. Default is |
constant_index |
Integer (length 1). Index of |
... |
Arguments passed down to |
A tibble with these columns:
x
and sd
, the group-wise reported input statistics, are repeated in
row pairs.
n
is dispersed from half the input n
, with n_change
tracking the
differences.
both_consistent
flags scenarios where both reported x
and sd
values
are consistent with the hypothetical n
values.
case
corresponds to the row numbers of the input data frame.
dir
is "forth"
in the first half of rows and "back"
in the second
half. "forth"
means that x2
and sd2
from the input are paired with the
larger dispersed n
, whereas "back"
means that x1
and sd1
are paired
with the larger dispersed n
.
Other columns from debit_map()
are preserved.
audit_total_n()
You can call
audit_total_n()
following up on debit_map_total_n()
to get a tibble with summary statistics. It will have these columns:
x1
, x2
, sd1
, sd2
, and n
are the original inputs.
hits_total
is the number of scenarios in which all of
x1
, x2
, sd1
, and sd2
are DEBIT-consistent. It is the sum
of hits_forth
and hits_back
below.
hits_forth
is the number of both-consistent cases that result
from pairing x2
and sd2
with the larger dispersed n
value.
hits_back
is the same, except x1
and sd1
are
paired with the larger dispersed n
value.
scenarios_total
is the total number of test scenarios,
whether or not both x1
and sd1
as well as x2
and sd2
are DEBIT-consistent.
hit_rate
is the ratio of hits_total
to scenarios_total
.
Call audit()
following audit_total_n()
to summarize results
even further.
Bauer, P. J., & Francis, G. (2021). Expression of Concern: Is It Light or Dark? Recalling Moral Behavior Changes Perception of Brightness. Psychological Science, 32(12), 2042–2043. https://journals.sagepub.com/doi/10.1177/09567976211058727
Heathers, J. A. J., & Brown, N. J. L. (2019). DEBIT: A Simple Consistency Test For Binary Data. https://osf.io/5vb3u/.
function_map_total_n()
, which created the present function using
debit_map()
.
# Run `debit_map_total_n()` on data like these:
df <- tibble::tribble(
~x1, ~x2, ~sd1, ~sd2, ~n,
"0.30", "0.28", "0.17", "0.10", 70,
"0.41", "0.39", "0.09", "0.15", 65
)
df
debit_map_total_n(df)
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