Re: random versus fixed factor
Dennis Roberts wrote: > 1. you could take several methods AT random (after you list out all 50) ... This is the classical position, I think. However, in practice we never require random sampling in order to treat people as random. Clark argues ISTR that we should treat factors as random if sampling them doesn't deplete the population being sampled. So people, words and so forth should be treated as random (if you wish to generalize beyond your sample). >From a pragmatic view Clark's position seems defensible - in that (whether sampling is random, pseudo-random or arbitrary) you will underestimate the error term if you treat factors as fixed in these circumstances. > maybe 3 ... and try ... and, if you find some differences amongst these 3 > ... then you might be able to generalize back to the entire set of 50 ... > ie, there are differences amongst the others too This seems an odd case. If you really wanted to generalize to only 50 methods I think you'd sample a different teaching method for each subject. This would allow you to generalize to people and methods simultaneously. (Sort of analagous to Clark's suggestion that you sample separate items for each participant to avoid needing to correct the F ratio). Thom = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
Re: random versus fixed factor
Elias wrote: Some have already been answered. > c) how formulas are changing? mean square between... (Ms) for mixed or > not designs? Random factors have extra variability associated with them compared to fixed factors. This variability reflects the fact that you are sampling a subset of items from from a population. The MSE term for random factors has an extra component reflecting this variability. > e) What is all about Clark and his experiment about verbs and noun? Clark argued that some experiments sample both subjects (people) and items (materials) from a population of possible people or items. In this case both people and items are random factors. The obvious example is sample words (say, nouns) from a language. If you use 30 words on a memory test and 30 people, Clark argued that to generalize your results to other people or other words wou need to treat both effects as random. > f) what is the relation of quasi F with fixed and random factor? Quasi F is the correct F ratio to use for two random effects. This is/was hard to calculate so Clark proposed a simple solution - calculate a minimum bound for quasi F - min F' using the F ratios obtained from two analyses - one treating subjects as random (the standard ANOVA) and one treating items as random and subjects fixed. minF' can only be significant if both these F ratios are significant But can fail to reach significance if both f ratios are significant). I minF' tends to be conservative (but only slightly in most cases, I think). > j) what happen about interaction eff? i read that if we have a random > factor we can have interaction without main effects. is right that? Do you mean the interaction is significant and the main effects are not? This is always possible. > k) And generally i read everywhere random versus fixed factor issue > but nowhere refer what is that (disadv, adv.. implications...), > neither i found something understadable in internet or in our > bibliothic. Look for the commentary to Clark's orginial article, e.g.: Clark, H. H. (1973). The language-as-fixed-effect fallacy: a critique of language statistics in psychological research. Journal of Verbal Learning and Verbal Behaviour, 12, 335-359. Wike, E. L., & Church, J. D. (1976). Comments on Clark's "The language-as-fixed-effect fallacy". Journal of Verbal Learning and Verbal Behaviour, 15, 249-255. Also recent articles such as: Raaijmakers, J. G. W., Schrijnemakers, J. M. C., & Gremmen, F. (1999). How to deal with "The language-as fixed-effect fallacy": Common misconceptions and solutions. Journal of Memory and Language, 41, 416-426. Thom = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
Re: random versus fixed factor
Elias <[EMAIL PROTECTED]> wrote: > hi > i am a little confused about this topic > (i am a student in psychology), i can not understand the below > (please be patient i am new to this) If you read Geoffrey Keppel _Design & Analysis. A Researcher's Handbook_, (the 2nd ed is ISBN 0-13-200048-2) this may answer a,b and c at least ;) -- | David Duffy. ,-_|\ | email: [EMAIL PROTECTED] ph: INT+61+7+3362-0217 fax: -0101/ * | Epidemiology Unit, The Queensland Institute of Medical Research \_,-._/ | 300 Herston Rd, Brisbane, Queensland 4029, Australia v = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
Re: random versus fixed factor
gee just a short question to answer! here is one part of it say you were interested in whether different teaching methods impacted on how well students learned intro statistics ... now, if we put our minds to it, there probably are 50 or more different ways we could teach a course like this but, there is no way you would be able to run an experiment trying out all 50 1. you could take several methods AT random (after you list out all 50) ... maybe 3 ... and try ... and, if you find some differences amongst these 3 ... then you might be able to generalize back to the entire set of 50 ... ie, there are differences amongst the others too 2. perhaps there are only 3 specific methods you have any interest in (out of the 50) ... and are not interested in any of the other 47. so, these specific 3 you use in your experiment and perhaps you find some differences. well, in this case ... you might be able to say that there ARE differences in these 3 but, you could not generalize to the larger set of the other 47 (since you did not sample representatively from all 50) #1 is called a random (independent variable) factor #2 is called a fixed (independent variable) factor At 02:39 PM 1/15/02 -0800, Elias wrote: >hi >i am a little confused about this topic > >= >Instructions for joining and leaving this list, remarks about the >problem of INAPPROPRIATE MESSAGES, and archives are available at > http://jse.stat.ncsu.edu/ >= = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
random versus fixed factor
hi i am a little confused about this topic (i am a student in psychology), i can not understand the below (please be patient i am new to this) if someone can tell me a) what is a fixed factor, whether we can treat a variable as fixed ? b) the same about random c) how formulas are changing? mean square between... (Ms) for mixed or not designs? d) Who is Keppel (i read him in many statistic papers but i can understood) and his contribution in statistic? e) What is all about Clark and his experiment about verbs and noun? f) what is the relation of quasi F with fixed and random factor? g) nested designs what are? h) What are the implications if a experiment have only 2 random factors, 2 fixed or 1 fixed and 1 random (and the changes in statistic types, MS...) i) when a experiment in anova has 3 factors, it could be all random? j) what happen about interaction eff? i read that if we have a random factor we can have interaction without main effects. is right that? k) And generally i read everywhere random versus fixed factor issue but nowhere refer what is that (disadv, adv.. implications...), neither i found something understadable in internet or in our bibliothic. l) so i ask sorry for all of these Q and for this person who will have the persistence to answere all these questions simply and understadible (i do not know if this place is suitable for these Q so i ask sorry for 2nd time) - i have bought the Howell D.C. book but do not tell much. - Also, i have access to some articles but all are very vague and no clear. -A GREAT THANK to anyone who will solve my querries -i must ask sorry for my englishs (i am Greek) Name: Elias email address: [EMAIL PROTECTED] = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
