d.ind.t.t {MOTE} | R Documentation |
d from t for Between Subjects
Description
This function displays d for between subjects data and the non-central confidence interval estimating from the t-statistic.
Usage
d.ind.t.t(t, n1, n2, a = 0.05)
Arguments
t |
t-test value |
n1 |
sample size group one |
n2 |
sample size group two |
a |
significance level |
Details
To calculate d, the t-statistic is multiplied by two then divided by the square root of the degrees of freedom.
d_s = 2 * t / sqrt(n1 + n2 - 2)
Learn more on our example page.
Value
Provides the effect size (Cohen's d) with associated confidence intervals, degrees of freedom, t-statistic, and p-value.
d |
effect size |
dlow |
lower level confidence interval of d value |
dhigh |
upper level confidence interval of d value |
n1 |
sample size |
n2 |
sample size |
df |
degrees of freedom (n1 - 1 + n2 - 1) |
t |
t-statistic |
p |
p-value |
estimate |
the d statistic and confidence interval in APA style for markdown printing |
statistic |
the t-statistic in APA for the t-test |
Examples
#The following example is derived from the "indt_data" dataset, included
#in the MOTE library.
#A forensic psychologist conducted a study to examine whether
#being hypnotized during recall affects how well a witness
#can remember facts about an event. Eight participants
#watched a short film of a mock robbery, after which
#each participant was questioned about what he or she had
#seen. The four participants in the experimental group
#were questioned while they were hypnotized. The four
#participants in the control group recieved the same
#questioning without hypnosis.
hyp = t.test(correctq ~ group, data = indt_data)
#You can type in the numbers directly, or refer to the dataset,
#as shown below.
d.ind.t.t(t = -2.6599, n1 = 4, n2 = 4, a = .05)
d.ind.t.t(-2.6599, 4, 4, .05)
d.ind.t.t(hyp$statistic,
length(indt_data$group[indt_data$group == 1]),
length(indt_data$group[indt_data$group == 2]),
.05)
#Contrary to the hypothesized result, the group that underwent hypnosis were
#significantly less accurate while reporting facts than the control group
#with a large effect size, t(6) = -2.66, p = .038, d_s = 2.17.