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N>=3 methods are used to measure each of n items. The data are used to estimate simultaneously systematic error (bias) and random error (imprecision). Observed measurements for each method or device are assumed to be linear functions of the unknown true values and the errors are assumed normally distributed. Pairwise calibration curves and plots can be easily generated. Unlike the 'ncb.od' function, the 'omx' function builds a one-factor measurement error model using 'OpenMx' and allows missing values, uses full information maximum likelihood to estimate parameters, and provides both likelihood-based and bootstrapped confidence intervals for all parameters, in addition to Wald-type intervals.
| Version: | 3.0 |
| Imports: | graphics, grDevices, stats, utils, OpenMx |
| Published: | 2023-08-29 |
| Author: | Richard A. Bilonick |
| Maintainer: | Richard A. Bilonick <rabilonick at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | merror results |
| Reference manual: | merror.pdf |
| Package source: | merror_3.0.tar.gz |
| Windows binaries: | r-devel: merror_3.0.zip, r-release: merror_3.0.zip, r-oldrel: merror_3.0.zip |
| macOS binaries: | r-release (arm64): merror_3.0.tgz, r-oldrel (arm64): merror_3.0.tgz, r-release (x86_64): merror_3.0.tgz, r-oldrel (x86_64): merror_3.0.tgz |
| Old sources: | merror archive |
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