precision.mle.ncb.od

This is an internal function that computes iterative approximation to mle precision estimates for nonconstant bias model using original 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

precision.mle.ncb.od function

<dl> <dt>x</dt>
<dd>A matrix or numeric data.frame consisting of an n (no. of items) by N (no. of methods) matrix of measuremnts. N must be &gt;= 3 and n &gt; N.</dd> <dt>M</dt>
<dd>Maximum no. of iterations for convergence.</dd> <dt>beta.bars</dt>
<dd>Estimates or hypothesized values for the betas.</dd> <dt>jaech.errors</dt>
<dd>TRUE replicates the minor error in Jaech's Fortran code to allow comparison with his
 examples.</dd></dl>

Arguments

Author

Computes iterative approximation to mle precision estimates for nonconstant bias model using original data. — precision.mle.ncb.od

<dl>

 <dt>x</dt>
<dd>A matrix or numeric data.frame consisting of an n (no. of items) by N (no. of methods) matrix of measuremnts. N must be &gt;= 3 and n &gt; N.</dd>

 <dt>M</dt>
<dd>Maximum no. of iterations for convergence.</dd>

 <dt>beta.bars</dt>
<dd>Estimates or hypothesized values for the betas.</dd>

 <dt>jaech.errors</dt>
<dd>TRUE replicates the minor error in Jaech's Fortran code to allow comparison with his
 examples.</dd>

</dl>

precision.mle.ncb.od: Computes iterative approximation to mle precision estimates for nonconstant bias model using original data.

Description

Usage

Value

Arguments

Author

Details

References

See Also