g.ind.t | R Documentation |
This function displays d-g corrected and the non-central confidence interval for independent t.
g.ind.t(m1, m2, sd1, sd2, n1, n2, a = 0.05)
m1 |
mean group one |
m2 |
mean group two |
sd1 |
standard deviation group one |
sd2 |
standard deviation group two |
n1 |
sample size group one |
n2 |
sample size group two |
a |
significance level |
The correction is calculated by dividing three by the sum of both sample sizes after multiplying by four and subtracting nine. This amount is deducted from one.
correction = 1 - (3 / (4 * (n1 + n2) - 9))
D-g corrected is calculated by substracting mean two from mean one, dividing by the pooled standard deviation which is multiplied by the correction above.
d_g corrected = ((m1 - m2) / spooled) * correction
Learn more on our example page.
D-g corrected with associated confidence intervals, the confidence intervals associated with the means of each group, standard deviations of the means for each group, relevant statistics.
d |
d-g corrected effect size |
dlow |
lower level confidence interval d-g corrected |
dhigh |
upper level confidence interval d-g corrected |
M1 |
mean group one |
sd1 |
standard deviation of group one |
se1 |
standard error of group one |
M1low |
lower level confidence interval of mean one |
M1high |
upper level confidence interval of mean one |
M2 |
mean two |
sd2 |
standard deviation of mean two |
se1 |
standard error of mean two |
M2low |
lower level confidence interval of mean two |
M2high |
upper level confidence interval of mean two |
spooled |
pooled standard deviation |
sepooled |
pooled standard error |
correction |
g corrected |
n1 |
size of sample one |
n2 |
size of sample two |
df |
degrees of freedom |
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 style for markdown printing |
#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. t.test(correctq ~ group, data = indt_data) #You can type in the numbers directly, or refer to the dataset, #as shown below. g.ind.t(m1 = 17.75, m2 = 23, sd1 = 3.30, sd2 = 2.16, n1 = 4, n2 = 4, a = .05) g.ind.t(17.75, 23, 3.30, 2.16, 4, 4, .05) g.ind.t(mean(indt_data$correctq[indt_data$group == 1]), mean(indt_data$correctq[indt_data$group == 2]), sd(indt_data$correctq[indt_data$group == 1]), sd(indt_data$correctq[indt_data$group == 2]), length(indt_data$correctq[indt_data$group == 1]), length(indt_data$correctq[indt_data$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_g = 1.64.
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