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Item-free person measurement means that the estimated trait levels for persons are not biased by the characteristics of the items For CTT, raw scores are directly dependent on item dif culty and other item properties For example, raw scores on an easy test are much higher than are raw scores on a hard test Even special equating does not fully handle dif culties arising from differing test dif culties (see Holland & Rubin, 1982) In IRT, item properties such as item dif culty are directly included in the model Thus, ability is estimated in the context of item parameters For example, a score of 5 on a test of 10 easy items will receive a much lower trait-level estimate than would the same score on a test of 10 hard items But as for item parameter calibrations, the standard errors of the person estimates are in uenced by item parameters.

That is, much larger standard errors will be found when the items are either much too hard or too easy for the person or when the items are not very discriminating Item-free person measurement is a central measurement property that makes adaptive testing feasible In adaptive testing, items are selected for each person to provide the most precise measurement If the item bank is large, few persons receive the same combination of items IRT can provide equated trait levels in this situation because the item-parameter estimates are controlled for in the estimation of the persons For adaptive testing, however, measurement error is minimized for everyone because of the optimal selection of items Special Properties of the Rasch Model Wright and colleagues (eg, Wright & Stone, 1979) have given much attention to conjoint measurement, a term rst used by Luce and Tukey (1964).

Conjoint measurement allows the scores of persons and items to be measured on the same scale (see Linacre & Wright, 2001) Originally, this scale used a logistic function, and the logistic is still the most often used No other mathematical formulation for the item ogives (ICCs) allows for independent estimation of item dif culty ( i ) and person trait level ( j ; Rasch, 1961) Other theoretical developments of the Rasch model s measurement properties stem from the European measurement tradition (see Fischer & Molenaar, 1995) Item-free person calibration for the Rasch model refers to a special relationship for this model and not the other IRT models Stated simply, the expected difference in performance between two persons on any item is given by the difference in their trait levels Speci cally, its meaning can be readily shown by the following: ln P(X i1 ) = 1 P(X i1 ).

To learn more about the bene ts of CVV2 and CVV2 technical requirements, contact the card association.

Thus, it is not an intrinsic characteristic of the system, but related to a speci c application and context This is achieved through the de nition of some parameters (supposing the parameters of integrity are available):.

1. Robert Kaplan and David Norton, The Balanced Scorecard: Measures That Drive Performance, Harvard Business Review (January February 1992). 2. Michael Hammer and James Champy, Reengineering the Corporation: A Manifesto for Business Revolution (New York: HarperBusiness, 2001). 3. Michael Hammer, The Agenda: What Every Business Must Do to Dominate the Decade (Three Rivers, MI: Three Rivers Press, 2003).

$ export CVSPATH= /var/lib/mythcvs $ export CVSROOT= :pserver:mythtv@cvs.mythtv.org:${CVSPATH} $ /usr/bin/cvs login Password: mythtv $ /usr/bin/cvs checkout r release-0-18 $ cd mythtv && ./configure && /usr/bin/make all $ /usr/bin/sudo make install Password:

The frame rate, the speed at which the animation is played, is measured in number of frames per second. A frame rate that s too slow makes the animation appear to stop and start; a frame rate that s too fast blurs the details of the animation. A frame rate of 12 frames per second (fps) usually gives the best results on the Web. QuickTime and AVI movies generally have a frame rate of 12 fps, while the standard motion-picture rate is 24 fps. The complexity of the animation and the speed of the computer on which the animation is being played affect the smoothness of the playback. Test your animations on a variety of machines to determine optimum frame rates.