<div>Hello Asonas!</div> <div>Normal distribution is something you MUST have? Why do you think that normality is a required characteristic of the particular population that you have tested? How are the mean and standard deviation? How are the skewness and kurtosis parameters? Please tell.</div> <div>I cannot qualify the scores of the students as "strange", as I dont't have additional information, but if you're normalizing something that is not normal, why are you interested to transform them until you get a normal distribution? You may sort the students according to their ability even if it is not normal distributed and if your test is a good one.</div> <div>What if your score distribution is multimodal? are you against that? high stakes tests may produce skewed or bimodal distributions, not normal, specially if teachers and the scholar program is looking to improve the results of the students.</div> <div>It is clear that many populations behave as a normal
distribution in various tests,but not necessarily in all tests.</div> <div>In addition, you must also have a uniform distribution of your items (are your items distributed according to a normal or to a uniform distribution?).</div> <div>And mainly, the most important of all, you must know if the test satisfies the specifications of validity, this is more important than normality of the distribution of the students.</div> <div>In brief: I am most interested in other things than normality, and certainly not in obtaining a "beautiful" picture of my students, I need before all to have a good test and get a "good" picture of the students. I can send you my picture, if the camera is a good one, and if I have a good picture, you must see an ugly man, I really don't expect a "beautiful" picture of myself, but a good one. Do I have to retouch my picture to have a "beautiful" man in my picture and say that I'm "normal"?</div> <div>Hope this helps</div>
<div>Regards</div> <div>Agustin Tristan<BR><BR><B><I>asonas lambrianou <email@example.com></I></B> wrote:</div> <BLOCKQUOTE class=replbq style="PADDING-LEFT: 5px; MARGIN-LEFT: 5px; BORDER-LEFT: #1010ff 2px solid">Dear friends,<BR>I have a very urgent question, anyone who can contribute, please do so<BR><BR>We use the t-scores (z scores) of the examinees on high stakes tests to sort them according to their ability. <BR>When the distribution of the raw scores deviates a lot from the normal, then the t-scores look a bit 'strange'. Do you also agree that t-scores can not be used when the distribution deviates substantially from the normal?<BR>Also, I can transform the raw scores using y=ln(x/(100-x)) and the distribution of the raw scores becomes normal. Then, I can get more 'beautiful' t scores (z scores). Am I allowed to use this transformation and then get the t scores?<BR><BR>Thanks<BR><BR>Jason<BR><BR><BR>> ----- Original Message -----<BR>> From: "Mike Linacre (RMT)"
<RMT@RASCH.ORG><BR>> To: firstname.lastname@example.org<BR>> Subject: [Rasch] Different models: counts to scale conversion<BR>> Date: Mon, 23 Jan 2006 14:58:51 -0600<BR>> <BR>> <BR>> Not sure about the contrast "log-scaled" vs. "Rasch-scaled"<BR>> <BR>> Georg Rasch based his theory on the Poisson model, which is a Rasch <BR>> model and is a log-scaling model. It seems the actual contrast is <BR>> between a Rasch-Poisson model and a Rasch rating-scale-type model.<BR>> <BR>> Mike L.<BR>> <BR>> Earlier remark:<BR>> > When I was predicting the amount of money that a counselor was <BR>> > going to be sued for a bad outcome based the hierarchical <BR>> > complexity of the informed consent procedure. Log money did the <BR>> > best. Right behind it by just a little worse .96 versus .94 was <BR>> > Rasch scaled money. The value of money has been argued to <BR>> > require loging for years.<BR>> <BR>>
_______________________________________________<BR>> Rasch mailing list<BR>> Rasch@acer.edu.au<BR>> http://listserv3.acer.edu.au/mailman/listinfo/rasch<BR><BR>><BR><BR><BR><BR>Dr. Iasonas Lamprianou<BR>CFAS, School of Education<BR>The University of Manchester<BR>Oxford Road, Manchester M13 9PL, UK<BR>Tel. 0044 161 275 3485<BR>email@example.com<BR><BR><BR><BR><BR>-- <BR>_______________________________________________<BR><BR>Search for businesses by name, location, or phone number. -Lycos Yellow Pages<BR><BR>http://r.lycos.com/r/yp_emailfooter/http://yellowpages.lycos.com/default.asp?SRC=lycos10<BR><BR>_______________________________________________<BR>Rasch mailing list<BR>Rasch@acer.edu.au<BR>http://listserv3.acer.edu.au/mailman/listinfo/rasch<BR></BLOCKQUOTE><BR><BR><BR><DIV><FONT color=#0000bf><STRONG>FAMILIA DE PROGRAMAS KALT. </STRONG></FONT></DIV>
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