## Comparing the reliability of related populations with the probability of agreement

## Abstract

Combining information from different populations to improve precision, simplify future predictions, or improve underlying understanding of relationships can be advantageous when considering the reliability of several related sets of systems. Using the probability of agreement to help quantify the similarities of populations can help to give a realistic assessment of whether the systems have reliability that are sufficiently similar for practical purposes to be treated as a homogeneous population. In addition, the new method is described and illustrated with an example involving two generations of a complex system where the reliability is modeled using either a logistic or probit regression model. Note that supplementary materials including code, datasets, and added discussion are available online.

- Authors:

- Univ. of San Francisco, San Francisco, CA (United States)
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

- Publication Date:

- Research Org.:
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

- Sponsoring Org.:
- USDOD; USDOE

- OSTI Identifier:
- 1304827

- Report Number(s):
- LA-UR-15-27900

Journal ID: ISSN 0040-1706

- Grant/Contract Number:
- AC52-06NA25396

- Resource Type:
- Accepted Manuscript

- Journal Name:
- Technometrics

- Additional Journal Information:
- Journal Name: Technometrics; Journal ID: ISSN 0040-1706

- Publisher:
- Taylor & Francis

- Country of Publication:
- United States

- Language:
- English

- Subject:
- 97 MATHEMATICS AND COMPUTING; generalized linear models; reliability; equivalence testing; homogeneity of population characteristics; probability of agreement

### Citation Formats

```
Stevens, Nathaniel T., and Anderson-Cook, Christine M. Comparing the reliability of related populations with the probability of agreement. United States: N. p., 2016.
Web. doi:10.1080/00401706.2016.1214180.
```

```
Stevens, Nathaniel T., & Anderson-Cook, Christine M. Comparing the reliability of related populations with the probability of agreement. United States. doi:10.1080/00401706.2016.1214180.
```

```
Stevens, Nathaniel T., and Anderson-Cook, Christine M. Tue .
"Comparing the reliability of related populations with the probability of agreement". United States. doi:10.1080/00401706.2016.1214180. https://www.osti.gov/servlets/purl/1304827.
```

```
@article{osti_1304827,
```

title = {Comparing the reliability of related populations with the probability of agreement},

author = {Stevens, Nathaniel T. and Anderson-Cook, Christine M.},

abstractNote = {Combining information from different populations to improve precision, simplify future predictions, or improve underlying understanding of relationships can be advantageous when considering the reliability of several related sets of systems. Using the probability of agreement to help quantify the similarities of populations can help to give a realistic assessment of whether the systems have reliability that are sufficiently similar for practical purposes to be treated as a homogeneous population. In addition, the new method is described and illustrated with an example involving two generations of a complex system where the reliability is modeled using either a logistic or probit regression model. Note that supplementary materials including code, datasets, and added discussion are available online.},

doi = {10.1080/00401706.2016.1214180},

journal = {Technometrics},

number = ,

volume = ,

place = {United States},

year = {2016},

month = {7}

}

*Citation information provided by*

Web of Science

Web of Science

Works referencing / citing this record:

##
Comparing the Reliability of Related Populations With the Probability of Agreement [Supplemental Data]

dataset, April 2017

- Stevens, Nathaniel; Anderson-Cook, Christine
- figshare-Supplementary information for journal article at DOI: 10.1080/00401706.2016.1214180, 1 PDF file (1.08 MB)

##
Comparing the Reliability of Related Populations with the Probability of Agreement v.1 [Supplemental Data]

dataset, July 2016

- Stevens, Nathaniel; Anderson-Cook, Christine
- Figshare-Supplementary information for journal article at DOI: 10.1080/00401706.2016.1214180, 1 PDF (1.08 MB)