MS Excel and statistics
Hi. I'd appreciate if someone can tell if there is any add-in or module for doing (a) studentized range tests, and (b) time series analysis in MS Excel? Thanks in advance. Regards, -- Ying-Foon Chow Department of Finance Tel: (+852) 2609 7638 The Chinese University of Hong KongFax: (+852) 2603 6586 Shatin, New Territories, Hong Kong Email: [EMAIL PROTECTED] === This list is open to everyone. Occasionally, less thoughtful people send inappropriate messages. Please DO NOT COMPLAIN TO THE POSTMASTER about these messages because the postmaster has no way of controlling them, and excessive complaints will result in termination of the list. For information about this list, including information about the problem of inappropriate messages and information about how to unsubscribe, please see the web page at http://jse.stat.ncsu.edu/ ===
Re: maximum likelihood factor analysis
[EMAIL PROTECTED] wrote: A self-report scale was constructed to measure work ethic and included three conceptually derived components of work ethic. Maximum likelihood factor analysis was then applied with the request of 3 factors to determine if the conceptually derived components actually represent empirical factors. Is this an appropriate/acceptable manner of evaluating the factor structure of the scale? Also, my version of SPSS (6.0) reports percent of variance accounted for by each factor, but doesn't indicate if this is common variance or total variance. Does someone know which variance is reported. Is maximum likelihood factor analysis used with either principle components or principal factors analysis? I would appreciate any explanation someone might offer. I have had difficulty finding any explanation on the web concerning these issues. Kary Kary: You might want to check out chapter 13 in Tabachnick, B.G., Fidell, L.S.(1996). Using multivariate statistics (3rd Edition). New York: Harper Collins. This chapter has a nice discussion of the differences and similarities between principal components and common factor analysis and it has some stuff on different estimation procedures. It sounds like you really want to do a confirmatory factor analysis in which you could specify which items load on which of the three factors. I don't think SPSS 6.0 will do CFA, but you may want to look into it anyway. HTH, Chuck -- Chuck Cleland Institute for the Study of Child Development UMDNJ-Robert Wood Johnson Medical School 97 Paterson Street New Brunswick, NJ 08903 phone: (732) 235-7699 fax: (732) 235-6189 http://www2.umdnj.edu/iscdweb/ -- === This list is open to everyone. Occasionally, less thoughtful people send inappropriate messages. Please DO NOT COMPLAIN TO THE POSTMASTER about these messages because the postmaster has no way of controlling them, and excessive complaints will result in termination of the list. For information about this list, including information about the problem of inappropriate messages and information about how to unsubscribe, please see the web page at http://jse.stat.ncsu.edu/ ===
Low Reliability.
Does any one know of good sources--either book chapters or articles--that discuss how low reliability among items in an experiment influences inferential statistics. Paul W. Jeffries Department of Psychology SUNY--Stony Brook Stony Brook NY 11794-2500 === This list is open to everyone. Occasionally, less thoughtful people send inappropriate messages. Please DO NOT COMPLAIN TO THE POSTMASTER about these messages because the postmaster has no way of controlling them, and excessive complaints will result in termination of the list. For information about this list, including information about the problem of inappropriate messages and information about how to unsubscribe, please see the web page at http://jse.stat.ncsu.edu/ ===
Markov Chain Monte Carlo Short Course
Short Course on Bayesian Modeling with Markov Chain Monte Carlo (MCMC) Methods Sponsored by the Chicago Chapter of the American Statistical Association June 1-2, 2000 The University of Chicago Gleacher Center Chicago IL USA This two-day course will provide participants with hands-on experience in applying Bayesian models using Markov Chain Monte Carlo (MCMC) simulation. MCMC has received increasing attention in recent years because it substantially broadens the range of problems that can be analyzed in the Bayesian framework. MCMC techniques like the Gibbs Sampler have found their way in to many application areas, including econometrics, biostatistics, marketing science, management science, education, environmental statistics, and psychometrics. The lead instructor for the course will be Peter Lenk, Associate Professor of Statistics and Management Science, The University of Michigan Business School. Example analyses and exercises will be done using GAUSS, a statistical and mathematical programming environment made available for use in the workshop by Aptech Systems, Inc. (www.aptech.com). Short course participants should be comfortable with computer programming, basic algebra, and simple distributions such as the normal and binomial distributions. Each participant will be asked to bring a notebook computer. For questions about computer configuration requirements, contact the Chapter using one of the methods indicated below. Admission: Members of the Chicago Chapter ASA: $450.00 Non Members of the Chicago Chapter: $475.00 Because this course concerns a topic of current high interest, we urge members to make their reservations early. We regret that we cannot accept reservations without payment of tuition and we also regret we cannot accept credit cards. Payment is to be by cash or check only. In order to reserve a seat, we must receive payment by May 1, 2000. Please make checks payable to "ASA-Chicago". Additional information may be found at http://www.chicagoASA.org. If there are more questions, please e-mail [EMAIL PROTECTED], call +1 773 702 0517, or send mail to: MCMC Short-Course, opNUMERICS 151 N. Kenilworth Suite 4A Oak Park, IL 60301 USA -- == Patrick J. Fleury, Ph.D.(773)-702-0517 General Clincal Research Center W-514A [EMAIL PROTECTED] === This list is open to everyone. Occasionally, less thoughtful people send inappropriate messages. Please DO NOT COMPLAIN TO THE POSTMASTER about these messages because the postmaster has no way of controlling them, and excessive complaints will result in termination of the list. For information about this list, including information about the problem of inappropriate messages and information about how to unsubscribe, please see the web page at http://jse.stat.ncsu.edu/ ===
Re: Which Way Should We Go
On Mon, 24 Apr 2000, Warren wrote, in response to Milo Schield: So, we must be forced to decide between two competing hypotheses? H0: Use classical hypothesis testing H1: Use Bayesian analysis Oh? Do you then believe that these two propositions are (1) mutually exclusive and (2) exhaustive ? (_I_ don't...) Is there enough evidence to reject the null? First, we'd need to agree on what constituters evidence... Or, what is the probability that the null is true if we reject it? And we cannot answer this question in any case. -- DFB. Donald F. Burrill [EMAIL PROTECTED] 348 Hyde Hall, Plymouth State College, [EMAIL PROTECTED] MSC #29, Plymouth, NH 03264 603-535-2597 184 Nashua Road, Bedford, NH 03110 603-471-7128 === This list is open to everyone. Occasionally, less thoughtful people send inappropriate messages. Please DO NOT COMPLAIN TO THE POSTMASTER about these messages because the postmaster has no way of controlling them, and excessive complaints will result in termination of the list. For information about this list, including information about the problem of inappropriate messages and information about how to unsubscribe, please see the web page at http://jse.stat.ncsu.edu/ ===
Prediction of rare events
I am looking for any information concerning the prediction of _rare_ events. I would very much appreciate any pointers to books, articles, work-in-progress, on-line resources, etc etc. Many thanks, al Sent via Deja.com http://www.deja.com/ Before you buy. === This list is open to everyone. Occasionally, less thoughtful people send inappropriate messages. Please DO NOT COMPLAIN TO THE POSTMASTER about these messages because the postmaster has no way of controlling them, and excessive complaints will result in termination of the list. For information about this list, including information about the problem of inappropriate messages and information about how to unsubscribe, please see the web page at http://jse.stat.ncsu.edu/ ===
Re: Advice ANOVA t-test
On Mon, 24 Apr 2000, Timothy Graves wrote: I could really use a little advice. I am preparing a research paper proposal for my M. Ed. I am not sure on a few issues: Is ANOVA is a suitable form of t-test to determine if there is any significant differences between the means of three different subject groups on a Likert scale instrument? Am I off base here? Any suggestions? 'Twould be nearer the mark to say that the t-test is the special case of ANOVA when there are only two groups. Is ANOVA suitable for your situation? Probably. Some would dispute that, if by "a Likert scale instrument" you mean a single bipolar scale with Likert-like responses. If you mean an instrument comprising a bunch of items, each item being Likert scaled, and you are summing (or, equivalently, averaging) a subject's responses to all those items, hardly anyone would argue against using ANOVA. The usual alternatives are less desirable for a variety of reasons, som eof which have recently been posted on the edstat list. I am also trying to decide upon what internal-consistency method is suitable to use in determining the Reliability of a Likert scale instrument? Kuder-Richardson approaches? Alpha Coefficient? Well, as some of my colleagues will cheerfully point out at the drop of a hat, "reliability" is not a characteristic of an instrument. However you choose to measure it, it reflects the behavior of a particular group of persons who have responded to the instrument, and thus depends on (inter alia) the homogeneity of the responding population(s), the homogeneity of the items in the instrument, etc. Do you have a compelling reason to obtain a reliability coefficient at all, or to settle on any particular one in your proposal? (I suppose a compelling reason is that one or more of your committee members demands such a thing; but I meant substantive or logical reasons.) What do you think you'd do with such a thing, once you'd got it? My general advice regarding proposals is not to promise more than you're sure you can deliver, not to commit yourself to any details that you can avoid, and not to belabor the obvious. If your proposal entails some comparison among several groups, ANOVA or an ANOVA-like procedure is obviously going to be required; you need not say so (unless you need more boiler plate than I would accept in a proposal!) in writing, and in oral questioning you need only indicate, rather off-handedly, that of course ANOVA is one obvious way to address such comparisons. But it is entirely imaginable that you will have other variables lurking around, perhaps even explicitly measured, and that some more general linear model than ANOVA would be useful to apply -- a variant of multiple linear regression, for example, of which ANOVA is a particular family of subsets. Is that Likert scale instrument something of your own devising, or is it an extant device of some sort? If it's original with you, your committee may well feel that some sort of instrument development phase might be desirable, or even necessary; though I wouldn't usually expect that at the M.Ed. level. If they do require you to do some of that, you'll need to know something about measurement in general, and should read up in some of the elementary texts in the area. (And if they do require anything of the sort, ask them whether the instrument-development phase would suffice for your magistral research. I've known that to be accepted in a Ph.D. proposal at OISE, when the area of proposed research really had no instruments to speak of, and the candidate was going to be spending a lot of time, energy, and theory on developing an instrument to measure what she needed to measure if she were ever going to carry out the research she had in mind in the first place. This is my first crack at this type of research, and any help in this regard would be greatly appreciated. Hope this has helped some. -- DFB. Donald F. Burrill [EMAIL PROTECTED] 348 Hyde Hall, Plymouth State College, [EMAIL PROTECTED] MSC #29, Plymouth, NH 03264 603-535-2597 184 Nashua Road, Bedford, NH 03110 603-471-7128 (Professor Emeritus, Department of MECA, OISE) === This list is open to everyone. Occasionally, less thoughtful people send inappropriate messages. Please DO NOT COMPLAIN TO THE POSTMASTER about these messages because the postmaster has no way of controlling them, and excessive complaints will result in termination of the list. For information about this list, including information about the problem of inappropriate messages and information about how to unsubscribe, please see the web page at
