16. Non-parametric Tests
16.3 Paired Sample Sign Test
Here we have two measurements from each subject, typically before and after. If the difference between measurements is , assign a
, if
, assign a
, if 0 assign a 0. (Be sure to keep the direction of subtraction consistent with the hypothesis.) We again have 2 cases, for small (
) and large (
) samples, as with the median sign test. The critical and test statistics are the same as the median sign test. We’ll work through an example with a small sample.
Example 16.5 : We have the following data on number of ear infections on swimmers before and after taking a medication that is hypothesized to prevent infections :
Swimmer | Infections before, ![]() |
Infections after, ![]() |
Difference (![]() |
A | 3 | 2 | + |
B | 0 | 1 | – |
C | 5 | 4 | + |
D | 4 | 0 | + |
E | 2 | 1 | + |
F | 4 | 3 | + |
G | 3 | 1 | + |
H | 5 | 3 | + |
I | 2 | 2 | 0 |
J | 1 | 3 | – |
In the last column, we have assigned when
,
when
and
when
. We are interested in reduced infections so
is “good” for this situation. Test if the reduction in infections is significant.
1. Hypothesis.
: MD difference
0
: MD difference
0
2. Critical statistic.
Use the Sign Test Critical Values Table with = (no. of
) + (no. of
) = 7 + 2 = 9 and
with a one-tailed test to find
3. Test statistic.
4. Decide.
so do not reject .
5. Interpretation.
There is not enough evidence to say that there is a reduction in the number of infections.
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