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help for ^mstdizem^
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Marginal standardization of two-way tables (matrix version)
-----------------------------------------------------------

    ^mstdizem^ matrix_input row_total_vector column_total_vector
    matrix_output [ ^, tol^erance^(^#^) f^ormat^(^%fmt^)^ ]

Description
-----------

^mstdizem^ takes matrix_input and produces matrix_output, which is
matrix_input scaled such that the row totals are given by
row_total_vector and the column totals given by column_total_vector.


Remarks
-------

The algorithm is

0. Initialise
         guess = matrix_input

1. Loop until max (| guess - previous guess |) <= tolerance
         previous guess = guess
         guess = diag(target row total / guess row total) * guess
         guess = guess * diag(target col total / guess col total)
   where * is matrix multiplication.

The total over rows of the column totals should equal the total over
columns of the row totals. That is, the two should lead to the same
grand total.

This procedure is known by many different names in several different
disciplines, including statistics, economics and engineering. Some are

    biproportional matrices
    iterative proportional fitting
    raking
    RAS technique

The data matrix may be entered directly into Stata or it may be produced
by a previous command, such as ^tabulate^.


Options
-------

^tolerance(^#^)^ is a technical option indicating the criterion for
    convergence. This is the largest acceptable absolute difference
    between each guess and the previous guess (and also between the two
    totals of totals). Default 0.001.

^format(^%fmt^)^ controls the format with which matrix_output is
    printed. Default format ^%9.2f^.


Examples
--------

    Data used by Smith (1976), quoted by Agresti (1990, p.197):
    . ^mat freq = (209,101,237\151,126,426\16,21,138)^
    . ^mat r = (100\100\100)^
    . ^mat c = (100,100,100)^
    . ^mstdizem freq r c Freq^

    Data used by Friedlander (1961), quoted by Bishop et al. (1975,
    p.98):
    . ^mat freq = (1306,83,0\619,765,3\263,1194,9\173,1372,28\^
        ^171,1393,51\159,1372,81\208,1350,108\1116,4100,2329)^
    . ^mat rt = (1412\1402\1450\1541\1681\1532\1662\7644)^
    . ^mat ct = (3988,11702,2634)^
    . ^mstdize freq rt ct Freq^

References
----------

Agresti, A. 1990. Categorical data analysis. New York: John Wiley.

Bishop, Y.M.M., Fienberg, S.E. and Holland, P.W. 1975. Discrete
multivariate analysis. Cambridge, MA: MIT Press.

Friedlander, D. 1961. A technique for estimating a contingency table
given the marginal totals and some supplementary data. Journal of the
Royal Statistical Society Series A 124: 412-420.

Smith, K.W. 1976. Table standardization and table shrinking: aids in the
traditional analysis of contingency tables. Social Forces 54, 669-693.


Author
------

         Nicholas J. Cox, University of Durham, U.K.
         n.j.cox@@durham.ac.uk

Also see
--------

On-line:  help for @mstdize@ (if installed)

