mandel.h is a convenience wrapper for mandel.kh(..., type="h"). It is generic, 
with methods for numeric vectors, arrays, data frames, matrices and objects of class 
'ilab'. All parameters are passed to mandel.kh.
Mandel's h is an indicators of relative deviation for grouped 
sets of observations. Given a set of observations \(x_{ijl}\) where \(i, j, l\)
denotes observation \(l\), \(l=1, 2, ... n\) for measurand or test item \(j\) and group
(usually laboratory) \(i\), \(i=1, 2, ... p\), Mandel's \(h\) is given by:
$$h=\frac{\bar{x_{ij}}-\bar{x_j}}{s_j}$$
where
\( s_j=\sqrt{\sum_{i=1}^p{\frac{(\bar{x_{ij}}-\bar{x_j})}{p-1}}}\)
If x is a vector, one-dimensional array or single-column matrix, values are aggregated 
by g and, if present, by m. If x is a data frame or matrix, each column 
is aggregated by g and m silently ignored if present. In all cases, if g
is NULL or missing, each row (or value, if a vector) in x 
is taken as a pre-calculated mean (for Mandel's \(h\)) or standard deviation (for Mandel's \(k\)).
If x is an object of class 'ilab', g defaults to '$org' and 
m to $measurand.
The returned object includes a label ('grouped.by') for the primary grouping factor. 
For the 'ilab' method, this is "Organisation". For other methods, If rowname is 
non-null, rowname is used. If rowname is NULL, the default is deparse(substitute(g));
if g is also NULL or missing, "Row" is used.
If method="robust", Mandel's \(h\) is replaced by a robust z score calculated by 
replacing \(\bar{x_j}\) and \(s_j\) with the robust estimates of location and scale 
obtained using Huber's estimate with tuning constant k set to 1.5 (unless otherwise 
specified in ...).