Statistical tools for analyzing clustered binary matched-pair data in
The tests and tools included in this package work primarily on
clustered binary matched-pair data. In order for data to be a good fit
for analysis with these tools it needs to have the following three
- Clustered (aka correlated,
non-independent): Multiple samples drawn from the same
- e.g. Measurements of multiple teeth from each of several dental
patients. The teeth of one patient are more likely to be similar than
the teeth of different patients.
- Binary (aka dichotomous): Results that can
have only two discrete values.
- e.g. Values like true/false, yes/no, success/failure,
- Matched-pair: Data points that come in pairs. Often
from successive trials in a repeated measures experiment or from
measuring two different, but related, sources.
- e.g. Eyes measured before and after surgery or the opinions of a
doctor and her patient on the patient’s progress.
This package contains 5 statistical tests suitable for analyzing
clustered binary matched-pair data in various contexts. Four of the
tests are designed specifically for this type of data. The fifth test,
McNemar’s test is the conceptual predecessor to each of the other tests,
and is included for comparison. In practice, McNemar’s test is
specifically noted to be unsuitable for clustered data. The tests are
listed below, along with the articles which introduce them:
- McNemar: McNemar, Quinn. 1947. “Note
on the sampling error of the difference between correlated proportions
or percentages.” Psychometrika.
- Eliasziw: Eliasziw, Michael, and
Allan Donner. 1991. “Application of the McNemar test to non‐independent
matched pair data.” Statistics in medicine.
- Obuchowski: Obuchowski,
Nancy A. 1998. “On the comparison of correlated proportions for
clustered data.” Statistics in medicine.
- Durkalski: Durkalski, Valerie L., Yuko
Y. Palesch, Stuart R. Lipsitz, and Philip F. Rust. 2003. “Analysis of
clustered matched‐pair data.” Statistics in medicine.
- Yang: Yang, Zhao, Xuezheng
Sun, and James W. Hardin. 2010. “A note on the tests for clustered
matched‐pair binary data.” Biometrical journal.
Included is sample data from real world experiments of the form that
can benefit from the application of these tests:
- Obfuscation: Programmers were asked to
hand-evaluate pairs of obfuscated and deobfuscated snippets of C source
code. The data is tested to see whether or not programmers trace
deobfuscated code any differently than obfuscated code.
- Psychiatry: Psychiatrists and their patients were
asked to evaluate the applicability of various concerns and treatments
to the patient. The data is tested to see how well patient and doctor
- Thyroids: Hyperparathyroidism patients were scanned
using both PET and SPECT tests. The data is tested to evaluate the
sensitivity and specificity of the two tomogoraphy tests.
Description of functions as well as usage examples are available in
Installation and Use
You can install the latest release from CRAN:
To use, load as follows: