d.prop: d for Independent Proportions

In doomlab/MOTE: Effect Size and Confidence Interval Calculator

d for Independent Proportions

Description

This function displays d and central confidence interval calculated from differences in independent proportions. Independent proportions are two percentages that are from different groups of participants.

Usage

d.prop(p1, p2, n1, n2, a = 0.05)

Arguments

p1	proportion for group one
p2	proportion for group two
n1	sample size group one
n2	sample size group two
a	significance level

Details

To calculate z, the proportion of group two is substracted from group one, which is then divided by the standard error.

z = (p1 - p2) / se

To calculate d, the proportion of group two is divided by the standard error of group two which is then subtracted from the proportion of group one divided by the standard error of group one.

z1 = p1 / se1

z2 = p2 / se2

d = z1 - z2

Learn more on our example page.

Value

d	effect size
dlow	lower level confidence interval d value
dhigh	upper level confidence interval d value
p1	proportion of group one
se1	standard error of the proportion of group one
z1	z-statistic group one
z1low	lower level confidence interval of z
z1high	upper level confidence interval of z
p2	proportion of group two
se2	standard error of the proportion of group two
z2	z-statistic of group two
z2low	lower level confidence interval of z
z2high	upper level confidence interval of z
n1	sample size group one
n2	sample size group two
z	z-statistic for the differences
ppooled	pooled proportion to calculate standard error
se	standard error
p	p-value for the differences
estimate	the d statistic and confidence interval in APA style for markdown printing
statistic	the t-statistic in APA style for markdown printing

Examples

#Several researchers were examining the data on the number
#of students who retake a course after they receive a D, F,
#or withdraw from the course. They randomly sampled form
#a large university two groups of students: traditional
#(less than 25 years old) and non-traditional (25 and older).
#Each group included 100 participants. About 25% of students
#of the traditional group reported they would retake a course,
#while the non-traditional group showed about 35% would
#retake the course.

#You can type in the numbers directly as shown below,
#or refer to your dataset within the function.

    d.prop(p1 = .25, p2 = .35, n1 = 100, n2 = 100, a = .05)

    d.prop(.25, .35, 100, 100, .05)

doomlab/MOTE documentation built on April 17, 2022, 2:08 a.m.