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From |
Maarten buis <maartenbuis@yahoo.co.uk> |

To |
stata list <statalist@hsphsun2.harvard.edu> |

Subject |
st: yet another update of hangroot available |

Date |
Mon, 23 Nov 2009 07:21:54 -0800 (PST) |

Thanks to Kit Baum a new version of the -hangroot- package is availabele from SSC. This update introduces the option to display a suspended rootogram rather than a hanging rootogram. This program can be installed by typing in Stata -ssc install hangroot-, or updated by typing -adoupdate, update- or -ssc install hangroot, replace-. Both graphs are designed graphically compare an empirical distribution to a theoretical distribution. The idea behind these graphs is best explained by showing example graphs. These can be seen here: <http://www.maartenbuis.nl/software/hangroot.html>. However, here is, for completenes sake, a verbal description of these graphs: The hanging rootogram draws the theoretical distribution and "hangs" the histogram bars representing the empricial distribution from it rather than "standing" these bars on the x-axis. This way deviations from the theoretical distribution are visible as deviations from the horizontal line y=0. This makes it easier to spot patterns in these deviations. The suspended rootogram takes this graph one step further. It recognizes that the key information in the hanging rootogram are not the histogram bars but its deviations from the line y=0, so why not disply these residuals directly? It than makes sense to flip the entire graph upside down, "suspending" the theoretical distribution from the x-axis, because positive residuals now represent too many observations in a bin and negative residuals represent too few. We can optionally suppress the display of the theoretical distribution, focussing entirely on the residuals. Another characteric of both the hanging rootogram and the suspended rootogram is that they are showing the freqencies on the square root scale. This way the sampling variation of the length of the bars representing the empirical distribution are stabelized. These lengths are counts of the number of observations that fall within each bin, and larger counts tend to have larger sampling variation than smaller counts, making it harder to compare the deviations across bins. By taking the square root, the sampling variations tends to be approximately equal across bins, facilitating the comparison across bins. Moreover, this tends to make deviations in the tails, where the counts are small, more visible. -- Maarten -------------------------- Maarten L. Buis Institut fuer Soziologie Universitaet Tuebingen Wilhelmstrasse 36 72074 Tuebingen Germany http://www.maartenbuis.nl -------------------------- * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

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