This is an internal function that computes the maximum likelihood estimates of precision for the constant
 bias model using paired data.

 htest

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.

Richard Bilonick

merror

Accuracy and Precision of Measurements

mle function

<dl> <dt>v</dt>
<dd>Variance-Covariance matrix for the n x N items by methods measurement data.</dd> <dt>r</dt>
<dd>Initial estimates of imprecision, usually Grubbs.</dd> <dt>ni</dt>
<dd>No. of items measured.</dd></dl>

Arguments

Author

Compute maximum likelihood estimates of precision. — mle

<dl>

 <dt>v</dt>
<dd>Variance-Covariance matrix for the n x N items by methods measurement data.</dd>

 <dt>r</dt>
<dd>Initial estimates of imprecision, usually Grubbs.</dd>

 <dt>ni</dt>
<dd>No. of items measured.</dd>

</dl>

mle: Compute maximum likelihood estimates of precision.

Description

Usage

Value

Arguments

Author

References