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I moved Rasch model, and a few other psychological and sociological terms, out of category:measurement because it seems inconsistent to have only a few topics on psychological measurement in the Category:Measurement, and the category appeared to be in some disarray. Especially as there is the Category:Psychometrics, which I made into a subcategory of measurement, since "Psychometrics is the field of study concerned with the theory and technique of psychological measurement" according to Psychometrics. So Rasch model and the few other topics which were in both Category:Psychometrics and category:measurement, are now just in Category:Psychometrics which is now a subcategory of measurement. Salsb 11:26, 28 September 2005 (UTC)
I edited the article to amend a poor use of English. You made a change to my edit, which reinstalled a poor use of English, so I reverted. I didn't notice that in that edit you had also included two new pars. I am sorry about that. But, that section excluded, you have now commented that "Changes made were factually incorrect". What changes were factually incorrect? Moriori 07:52, 30 November 2005 (UTC)
Dear Holon, both intro to Quantity page must be somehow merged; for as now its not good: the definition is not strong, quantity is not a relation, etc. I wait your combined version today. Thanks —The preceding unsigned comment was added by Azamat Abdoullaev ( talk • contribs) 08:45, 24 February 2006 (UTC)
I am not going ahead but waiting your version of merging of the introduction to Quantity. Below is my part.
'Quantity is among the basic classes of things along with quality, substance, change, and relation. Initially, quantity was introduced as quantum, an entity having quantity. Generally, quantity is viewed as the basic property of things existing as magnitudes or multitudes, or the state of being much. Being a fundamental term, quantity is used to refer to any type of quantitative properties or attributes of things. Of entities which pertain to quantities, some are such by their inner nature (as number), while others are functioning as states (properties, dimensions, attributes) and modifications like as heavy and light, long and short, broad and narrow, small and great, or much and little. Two basic differences of quantity, magnitude and multitude (or number), imply the principal distinction between continuity (continuum) and discontinuity. Under the names of multitude come what is discontinuous and discrete and divisible into indivisibles, all cases of collective nouns: army, fleet, flock, government, company, party, people, chorus, crowd, mess, and number. Under the names of magnitude come what is continuous and unified and divisible into divisibles, all cases of common names or mass nouns: the universe, matter, mass, energy, liquid, material, animal, plant, tree.'
Azamat Abdoullaev, 24 February 2006
Dear Holon,
I understand that you would like to retain some details in the criticism section of the entry Stevens' power law. In this context I would like to point out a couple of things.
I have reformulated the entry to both incorporate what you wanted to retain as well as the rest of Narens' (1996) results. Specifically, I've spelled out Narens' (1996) multiplicative property, and the associated (negative) empirical results. I have also added his commutative property and the associated (positive) results. Together, these show that Stevens' assumption of veridical judgments of numbers is wrong, but ratio scaled judgments seem correct. I've also added recent empirical results on the power law in the context of axiomatic psychophysics (when will someone write an entry on that discipline?).
I hope you will find this to include what you wanted to retain.
( Rutuag 07:03, 24 June 2006 (UTC))
Thanks -- I hope you won't take anything I say as anything other than for the sake of clarification and refinement. I think it is good to discuss these things. Mostly, I'm happy with the changes. I do not like the wording "veridical interpretation of numbers". Can you clarify what this means? The point is not how numbers are interpreted; it is whether the numbers are measurements of perceptions. If this is exactly the way it is stated in the literature on axiomatic psychophysics, fair enough, though I think it is very misleading.
"Without assuming veridical interpretation of numbers, Narens (1996) formulated another property that, if sustained, meant that respondents could make ratio scaled judgments, namely, if y is judged p times x, z is judged q times y, and if y' is judged q times x, z' is judged p times y', then z should equal z'. This property has been sustained in a variety of situations (Ellermeier & Faulhammer, 2000; Zimmer, 2005)."
I will try to get hold of this reference. First, I do not follow how this is "without assuming veridical interpretation of numbers". I'll await clarification of the point above. Second, are you able to describe the methods used? I find it difficult to believe there is any compelling evidence it is possible to get ratio measurements of perceived magnitudes, particularly just by "judging numbers". Thanks again. Holon 11:05, 24 June 2006 (UTC)
By the way, I forgot to say -- you should write an article on axiomatic psychophysics if you are able. There was nothing on Rasch measurement before I added articles. Having articles depends on contributors like you who know the area. So I hope you will contribute material in this area if you can. Regards Holon 11:10, 24 June 2006 (UTC)
( Rutuag 05:27, 27 June 2006 (UTC))
You take my words too literally. If I were arguing Stevens' version of measurement and that to be the end of it, we wouldn't be having this conversation. The entire thrust of the discussion is what underlay his methodology.
I can't think of a better way to cast the problems of this than by the following "The failure of measurement to "take" in cognition and psychometrics is related to a deep conceptual question concering the relationship between statistics, as away of describing randomness, and measurement, as a way of describing structure. The lack of an adequate theory for this relationship is, in reality, a weakness of both fields."
I think it vital not to confuse foundational issues of measurement and approaches to measurement: in this context it is perhaps instructive to quote Michell, "The measurability thesis, the rock upon which quantitative psychology is built, and conjoint measurement theory, psychology's best chance of checking the foundations upon which this rock stands..." (Michell, 1999, p. 213).
I am unsure as to what you are getting at here. It sounds as if you are a priori sceptical about what has been discussed but will not let that deter you from further exploration. The company of Suppes, Krantz, Tversky, Tukey, Luce, Narens, and others is well worth a visit. The other part of what you write seems to hark back to the issue of error in measurement. I talked some about that in the above and some more in the following.
Michell (1999) writes, "...this prediction provides a specific test of the hypothesis that the attributes are quantitative...this test is called the Thomsen condition...a key condition in the theory of conjoint measurement...the important point is that a way, distinct from extensive measurement, had been specified whereby the hypothesis that an attribute has additive structure could be tested." (pp. 202-203). This is the same point as I attempted to make.
As to the question of "unit of psychological measurement" I really don't know what you mean. What is the unit of physical measurement? How is that answerable in absence of a scale? Or are you talking about some Fechnerian ideas such as JND's? I'm quite mystified by what you are saying here, but would like to understand.
I took a brief look at the first chapter of your thesis and from it I see that you are concerned with issues of maintaining the same scale across measurements. Indeed! I may read more. One thing caught my eye which relates directly to what we are talking about, namely invariances. Ratio invariance is what is needed to get ratio scales. That is testible upto the error of estimation and is a the heart of Naren's (1996) commutative property, Luce's (2002) proportion commuativity and both are quite well sustained in audition.
On a more light-hearted note, let me illustrate what I mean about units of measurement with a fictional story. There is a captain of a ship, and he is about to go to war. He wants to take as much coal as possible with him, but his men must travel 100 miles to get the coal. So he asks them a scientist to carefully measure how much mass the ship can take and then to also measure the coal. The scientist has the men load a large quantity of stone onto the ship. He has people judge many different quantities of stone against each other, and finds that is data meet the requirements of measurement. He then has someone travel and conduct similar experiments with the coal, and again he finds he can measure the coal. He reports back, saying that the measure of stone the ship can hold is 233, saying "we have also been able to measure the coal".
Captain: so then, how much coal can the ship hold?
Scientist: Sir, I don't know.
Captain: What do you mean you don't know, I asked you to measure how much mass the ship can hold and to measure the coal.
Scientist: Yes sir, we have done that.
Captain: Then what is the problem?
Scientist: Sir, there is know way of knowing what measurement of coal is equal to the measurement of stone the ship can hold.
The moral of the story is, I hope, obvious. This situation is simply ridiculous. Physical measurements are all but meaningless without knowledge of the unit. As Joel Michell says: "scientific measurement is properly defined as the estimation or discovery of the ratio of some magnitude of a quantitative attribute to a unit of the same attribute" (Michell, 1997, p. 358). See pp. 23-5 of my thesis for emphasis on how fundamental uits of measurement are to all of the physical sciences.
I must be very clear though, my view is that ignoring the importance of a unit has been a problem in measurement theory quite generally. Psychometrics is terrible in this respect as far as I'm concerned. Take care Holon 05:48, 28 June 2006 (UTC)
Hello, (I saw you were discussing psychometrics on the IRT-article) I'm currently doing my master thesis and its related to psychometrics. I'm currently examining a new test that uses computer adaptive testing. I have, however, stumbled upon some issues with the way the algorithm of the test works that makes a factor analysis approach chaotic and the approach I've used for getting a reliability is hard to understand. The latter is an approach I got from the test-creators. So, why do I put this here? Since you do psychometrics, maybe you know something about this issue that you can help me with. That is, point me in the direction of relevant literature or search terms etc. I'm looking for articles that describe how you can do a factor analysis even when you work with weighted items. that is, during the scoring of the test, all items gets an extra weight multiplied to their rawscore based on their overall importance decided by the scorer when he scores. So, items that are highly scores, increases, while low scored items are not that much improved. This weighting is hard to account for in a factor analysis. Do you know of any theory that discussesd weighted items, group dependent items, item dependen groups, item dependency etc? Because this is a real challenge for me... I know the information I have given you is sketchy, but maybe you know literature that touches the area...
thank you for your time. Thomasrm 14:43, 4 October 2006 (GMT1)
Could you send me an email using the wiki email function? I'm flat out right now but will get back to you soon as possible. Holon 04:16, 5 October 2006 (UTC)
Hi Holon, some time ago you posted your comments & suggestions on assessment, in particular the development of more rigorous rubrics and carefully designed examples. I didn't forget this suggestion, I was simply too busy to work on that issue at the time. We now have over 10% (and growing!) of the English Wikipedia assessed via this scheme, so it's getting to be pretty important! I also think we'll start seeing press stories mentioning it, so I'd like the system to be able to stand up to public scrutiny, even if it is a fairly rough scheme. Things on WP should lighten up for me in a week or two. Would you be willing to work on this with me? Please let me know, thanks again for sharing your ideas, Walkerma 05:35, 9 November 2006 (UTC)
OK, I think we have enough people to make a start on this initiative. Can you help? I'm proposing that we start with your idea, and once we have the detailed description with lots of exemplars we can distil that to get the simplified version. Does this sound OK? If so, would you like to suggest what specifically we should do first? Cheers, Walkerma ( talk) 03:13, 8 May 2008 (UTC)
Holon - This is a REALLY good article, but it lacks inline references. It's probably just a matter of time until somebody tags it. I might be able to help with this, and I'm kind of wondering -- Do you know how to do inline references? Do the references at the end lend themselves to being put in line? Etc. Regards, Lou Sander ( talk) 13:29, 31 December 2008 (UTC)
You said on my talk page:
Let's take the two articles separately. "Empirical statistical laws" did indeed lack citations, but it might have been better to add a citation tag rather than AfD. On "regression to the mean" you seem to want incredibly fine definition of every jot and tittle in the lede section. The sentence was meant to say why the concept is important, which is what a lede section is meant to include. For readability's sake it is necessary to keep the lede clear of pedantic definitions and ciations that would be better placed in the main part of the article. For example, one might take Rasch model (which appears on your user page as something started by you) and notice just how many undefined terms there are in the lede section. Melcombe ( talk) 13:59, 30 July 2009 (UTC)
Would you mind taking another look at WP:AFDHOWTO and completing the steps you missed out? At the moment this AfD is not included in any of the WP:AfD#Current discussions logs so won't be noticed by many who contribute to these discussions. (Sometimes a bot fixes a missed step, but it appears this one has escaped its notice too.) I'd suggest also including it at WP:WikiProject Deletion sorting/Science. Regards, Qwfp ( talk) 10:37, 31 July 2009 (UTC)
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Redwolf24 9 July 2005 08:48 (UTC)
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I moved Rasch model, and a few other psychological and sociological terms, out of category:measurement because it seems inconsistent to have only a few topics on psychological measurement in the Category:Measurement, and the category appeared to be in some disarray. Especially as there is the Category:Psychometrics, which I made into a subcategory of measurement, since "Psychometrics is the field of study concerned with the theory and technique of psychological measurement" according to Psychometrics. So Rasch model and the few other topics which were in both Category:Psychometrics and category:measurement, are now just in Category:Psychometrics which is now a subcategory of measurement. Salsb 11:26, 28 September 2005 (UTC)
I edited the article to amend a poor use of English. You made a change to my edit, which reinstalled a poor use of English, so I reverted. I didn't notice that in that edit you had also included two new pars. I am sorry about that. But, that section excluded, you have now commented that "Changes made were factually incorrect". What changes were factually incorrect? Moriori 07:52, 30 November 2005 (UTC)
Dear Holon, both intro to Quantity page must be somehow merged; for as now its not good: the definition is not strong, quantity is not a relation, etc. I wait your combined version today. Thanks —The preceding unsigned comment was added by Azamat Abdoullaev ( talk • contribs) 08:45, 24 February 2006 (UTC)
I am not going ahead but waiting your version of merging of the introduction to Quantity. Below is my part.
'Quantity is among the basic classes of things along with quality, substance, change, and relation. Initially, quantity was introduced as quantum, an entity having quantity. Generally, quantity is viewed as the basic property of things existing as magnitudes or multitudes, or the state of being much. Being a fundamental term, quantity is used to refer to any type of quantitative properties or attributes of things. Of entities which pertain to quantities, some are such by their inner nature (as number), while others are functioning as states (properties, dimensions, attributes) and modifications like as heavy and light, long and short, broad and narrow, small and great, or much and little. Two basic differences of quantity, magnitude and multitude (or number), imply the principal distinction between continuity (continuum) and discontinuity. Under the names of multitude come what is discontinuous and discrete and divisible into indivisibles, all cases of collective nouns: army, fleet, flock, government, company, party, people, chorus, crowd, mess, and number. Under the names of magnitude come what is continuous and unified and divisible into divisibles, all cases of common names or mass nouns: the universe, matter, mass, energy, liquid, material, animal, plant, tree.'
Azamat Abdoullaev, 24 February 2006
Dear Holon,
I understand that you would like to retain some details in the criticism section of the entry Stevens' power law. In this context I would like to point out a couple of things.
I have reformulated the entry to both incorporate what you wanted to retain as well as the rest of Narens' (1996) results. Specifically, I've spelled out Narens' (1996) multiplicative property, and the associated (negative) empirical results. I have also added his commutative property and the associated (positive) results. Together, these show that Stevens' assumption of veridical judgments of numbers is wrong, but ratio scaled judgments seem correct. I've also added recent empirical results on the power law in the context of axiomatic psychophysics (when will someone write an entry on that discipline?).
I hope you will find this to include what you wanted to retain.
( Rutuag 07:03, 24 June 2006 (UTC))
Thanks -- I hope you won't take anything I say as anything other than for the sake of clarification and refinement. I think it is good to discuss these things. Mostly, I'm happy with the changes. I do not like the wording "veridical interpretation of numbers". Can you clarify what this means? The point is not how numbers are interpreted; it is whether the numbers are measurements of perceptions. If this is exactly the way it is stated in the literature on axiomatic psychophysics, fair enough, though I think it is very misleading.
"Without assuming veridical interpretation of numbers, Narens (1996) formulated another property that, if sustained, meant that respondents could make ratio scaled judgments, namely, if y is judged p times x, z is judged q times y, and if y' is judged q times x, z' is judged p times y', then z should equal z'. This property has been sustained in a variety of situations (Ellermeier & Faulhammer, 2000; Zimmer, 2005)."
I will try to get hold of this reference. First, I do not follow how this is "without assuming veridical interpretation of numbers". I'll await clarification of the point above. Second, are you able to describe the methods used? I find it difficult to believe there is any compelling evidence it is possible to get ratio measurements of perceived magnitudes, particularly just by "judging numbers". Thanks again. Holon 11:05, 24 June 2006 (UTC)
By the way, I forgot to say -- you should write an article on axiomatic psychophysics if you are able. There was nothing on Rasch measurement before I added articles. Having articles depends on contributors like you who know the area. So I hope you will contribute material in this area if you can. Regards Holon 11:10, 24 June 2006 (UTC)
( Rutuag 05:27, 27 June 2006 (UTC))
You take my words too literally. If I were arguing Stevens' version of measurement and that to be the end of it, we wouldn't be having this conversation. The entire thrust of the discussion is what underlay his methodology.
I can't think of a better way to cast the problems of this than by the following "The failure of measurement to "take" in cognition and psychometrics is related to a deep conceptual question concering the relationship between statistics, as away of describing randomness, and measurement, as a way of describing structure. The lack of an adequate theory for this relationship is, in reality, a weakness of both fields."
I think it vital not to confuse foundational issues of measurement and approaches to measurement: in this context it is perhaps instructive to quote Michell, "The measurability thesis, the rock upon which quantitative psychology is built, and conjoint measurement theory, psychology's best chance of checking the foundations upon which this rock stands..." (Michell, 1999, p. 213).
I am unsure as to what you are getting at here. It sounds as if you are a priori sceptical about what has been discussed but will not let that deter you from further exploration. The company of Suppes, Krantz, Tversky, Tukey, Luce, Narens, and others is well worth a visit. The other part of what you write seems to hark back to the issue of error in measurement. I talked some about that in the above and some more in the following.
Michell (1999) writes, "...this prediction provides a specific test of the hypothesis that the attributes are quantitative...this test is called the Thomsen condition...a key condition in the theory of conjoint measurement...the important point is that a way, distinct from extensive measurement, had been specified whereby the hypothesis that an attribute has additive structure could be tested." (pp. 202-203). This is the same point as I attempted to make.
As to the question of "unit of psychological measurement" I really don't know what you mean. What is the unit of physical measurement? How is that answerable in absence of a scale? Or are you talking about some Fechnerian ideas such as JND's? I'm quite mystified by what you are saying here, but would like to understand.
I took a brief look at the first chapter of your thesis and from it I see that you are concerned with issues of maintaining the same scale across measurements. Indeed! I may read more. One thing caught my eye which relates directly to what we are talking about, namely invariances. Ratio invariance is what is needed to get ratio scales. That is testible upto the error of estimation and is a the heart of Naren's (1996) commutative property, Luce's (2002) proportion commuativity and both are quite well sustained in audition.
On a more light-hearted note, let me illustrate what I mean about units of measurement with a fictional story. There is a captain of a ship, and he is about to go to war. He wants to take as much coal as possible with him, but his men must travel 100 miles to get the coal. So he asks them a scientist to carefully measure how much mass the ship can take and then to also measure the coal. The scientist has the men load a large quantity of stone onto the ship. He has people judge many different quantities of stone against each other, and finds that is data meet the requirements of measurement. He then has someone travel and conduct similar experiments with the coal, and again he finds he can measure the coal. He reports back, saying that the measure of stone the ship can hold is 233, saying "we have also been able to measure the coal".
Captain: so then, how much coal can the ship hold?
Scientist: Sir, I don't know.
Captain: What do you mean you don't know, I asked you to measure how much mass the ship can hold and to measure the coal.
Scientist: Yes sir, we have done that.
Captain: Then what is the problem?
Scientist: Sir, there is know way of knowing what measurement of coal is equal to the measurement of stone the ship can hold.
The moral of the story is, I hope, obvious. This situation is simply ridiculous. Physical measurements are all but meaningless without knowledge of the unit. As Joel Michell says: "scientific measurement is properly defined as the estimation or discovery of the ratio of some magnitude of a quantitative attribute to a unit of the same attribute" (Michell, 1997, p. 358). See pp. 23-5 of my thesis for emphasis on how fundamental uits of measurement are to all of the physical sciences.
I must be very clear though, my view is that ignoring the importance of a unit has been a problem in measurement theory quite generally. Psychometrics is terrible in this respect as far as I'm concerned. Take care Holon 05:48, 28 June 2006 (UTC)
Hello, (I saw you were discussing psychometrics on the IRT-article) I'm currently doing my master thesis and its related to psychometrics. I'm currently examining a new test that uses computer adaptive testing. I have, however, stumbled upon some issues with the way the algorithm of the test works that makes a factor analysis approach chaotic and the approach I've used for getting a reliability is hard to understand. The latter is an approach I got from the test-creators. So, why do I put this here? Since you do psychometrics, maybe you know something about this issue that you can help me with. That is, point me in the direction of relevant literature or search terms etc. I'm looking for articles that describe how you can do a factor analysis even when you work with weighted items. that is, during the scoring of the test, all items gets an extra weight multiplied to their rawscore based on their overall importance decided by the scorer when he scores. So, items that are highly scores, increases, while low scored items are not that much improved. This weighting is hard to account for in a factor analysis. Do you know of any theory that discussesd weighted items, group dependent items, item dependen groups, item dependency etc? Because this is a real challenge for me... I know the information I have given you is sketchy, but maybe you know literature that touches the area...
thank you for your time. Thomasrm 14:43, 4 October 2006 (GMT1)
Could you send me an email using the wiki email function? I'm flat out right now but will get back to you soon as possible. Holon 04:16, 5 October 2006 (UTC)
Hi Holon, some time ago you posted your comments & suggestions on assessment, in particular the development of more rigorous rubrics and carefully designed examples. I didn't forget this suggestion, I was simply too busy to work on that issue at the time. We now have over 10% (and growing!) of the English Wikipedia assessed via this scheme, so it's getting to be pretty important! I also think we'll start seeing press stories mentioning it, so I'd like the system to be able to stand up to public scrutiny, even if it is a fairly rough scheme. Things on WP should lighten up for me in a week or two. Would you be willing to work on this with me? Please let me know, thanks again for sharing your ideas, Walkerma 05:35, 9 November 2006 (UTC)
OK, I think we have enough people to make a start on this initiative. Can you help? I'm proposing that we start with your idea, and once we have the detailed description with lots of exemplars we can distil that to get the simplified version. Does this sound OK? If so, would you like to suggest what specifically we should do first? Cheers, Walkerma ( talk) 03:13, 8 May 2008 (UTC)
Holon - This is a REALLY good article, but it lacks inline references. It's probably just a matter of time until somebody tags it. I might be able to help with this, and I'm kind of wondering -- Do you know how to do inline references? Do the references at the end lend themselves to being put in line? Etc. Regards, Lou Sander ( talk) 13:29, 31 December 2008 (UTC)
You said on my talk page:
Let's take the two articles separately. "Empirical statistical laws" did indeed lack citations, but it might have been better to add a citation tag rather than AfD. On "regression to the mean" you seem to want incredibly fine definition of every jot and tittle in the lede section. The sentence was meant to say why the concept is important, which is what a lede section is meant to include. For readability's sake it is necessary to keep the lede clear of pedantic definitions and ciations that would be better placed in the main part of the article. For example, one might take Rasch model (which appears on your user page as something started by you) and notice just how many undefined terms there are in the lede section. Melcombe ( talk) 13:59, 30 July 2009 (UTC)
Would you mind taking another look at WP:AFDHOWTO and completing the steps you missed out? At the moment this AfD is not included in any of the WP:AfD#Current discussions logs so won't be noticed by many who contribute to these discussions. (Sometimes a bot fixes a missed step, but it appears this one has escaped its notice too.) I'd suggest also including it at WP:WikiProject Deletion sorting/Science. Regards, Qwfp ( talk) 10:37, 31 July 2009 (UTC)
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