Description Usage Arguments Details Examples
This function will calculate d prime from a vector of hits and a vector of false alarms.
1 |
data |
A data frame. |
h |
A vector of hits (0 = miss, 1 = hit). |
f |
A vector of false alarms (0 = correct rejection, 1 = false alarm). |
This metric is common in discrimination experiments. Note: If your participants are at ceiling, you may want to consider another analysis.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | # Create some data
set.seed(1); library(dplyr)
axb <- data.frame(subj = sort(rep(1:10, each = 20, times = 10)),
group = gl(2, 1000, labels = c("g1", "g2")),
hit = c(rbinom(1000, size = c(0, 1), prob = .8),
rbinom(1000, size = c(0, 1), prob = .6)),
fa = c(rbinom(1000, size = c(0, 1), prob = .3),
rbinom(1000, size = c(0, 1), prob = .4))
)
# Calculate d prime on entire data frame
dPrime(axb, hit, fa)
# Calculate d prime for each subject by group, plot it,
# and run a linear model
library(dplyr)
axb %>%
group_by(subj, group) %>%
summarize(dp = dPrime(., hit, fa)) %T>%
{
plot(dp ~ as.numeric(group), data = .,
main = "d' as a function of group", xaxt = "n",
xlab = "Group", ylab = "d' prime")
axis(1, at = 1:2, labels = c("g1", "g2"))
abline(lm(dp ~ as.numeric(group), data = .), col = "red")
} %>%
lm(dp ~ group, data = .) %>%
summary()
|
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