The name is absent

Stata Technical Bulletin

overlap! is an immediate version of overlap. For the case of equal variances, the syntax is

overlap! mean1 mean2 sd

where sd is the common standard deviation of the two variables. For the case of unequal variances, the syntax is
overlap! mean1 mean2 sd1 sd2 (sd1 ≠ sd2)

For the general case, the syntax is

overlap! mean1 mean2 sd1 sd2 n1 n2

where n1 and n2 are the numbers of observations used to estimate the means and standard deviations of the two variables. This
syntax displays both the equal and unequal variance versions of the overlapping coefficient.

Example

As an example, we compare the distributions of fuel efficiency of foreign and domestic cars in the automobile data set
supplied with Stata. We begin by calculating the t test of the null hypothesis that the average miles per gallon is the same for
both sets of cars.

. use ∖stata∖auto, clear

The t test reveals a highly significant difference between the average mileage for foreign cars (24.8 MPG) and the average
mileage for domestic cars (19.8 MPG). However, the variance of MPG seems a bit higher for the foreign cars. Since the default
t test assumes equal variances across groups, we investigate further to see whether this assumption is justified.

. sdtest mpg, by(foreign)

The evidence is mixed: the p value of the test statistic is 5.5 percent. Since we are not sure whether the variances are equal,
we calculate the unequal variance version of the t test, to see if the apparent significance of the mileage difference is sensitive
to the assumption of equal variances.

. ttest mpg, by(foreign) unequal
Variable I       Obs        Mean   Std. Dev.

---------₊---------------------------------

0 I        52    19.82692    4.743297

1 I        22    24.77273    6.611187

---------₊---------------------------------
combined I       74     21.2973

Ho: mean(x) = mean(y) (assuming unequal variances)
t = -3.18 with 31 d.f.

Pr > ∣t∣ = 0.0033

<<   10   11   12   13   14   15   16   >>

More intriguing information