factor Analysis
Hi, I've got a question. Does anyone know how to set object in 2-factor dimensional space i.e I have 2 factor score. Therefore I can put variables in this space. But variables describe objects (i.e. these are 12 consumer products) and I don't care variables in space but only these products. I heard that factor score for a product is equal to product of the suitable factor loadings and variables mean. i.e. f(m,p)=a(1,m)u(1,p) +a(2,m)u(2,p)+ ...+a(j,m)u(j,p) where: f(m,d) - factor score for m-factor, p-th - consumer product , u(*) - mean for variable j and product p. Could you tell me is this true? How to proof this formally Huxley = 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: CONTENT ANALYSIS
Luis, I suggests you starts with the following site: http://www.gsu.edu/~wwwcom/ From there, you can get links to CONTENT, the internet mailing list and to several other web sites including these excellent ones: http://academic.csuohio.edu/kneuendorf/content An extensive site that supports users of Neuendorf's The Content Analysis Guidebook. http://www.content-analysis.de/ Matthias Romppel's rather large and useful site. www.textanalysis.info Harald Klein's site provides useful information regarding software for text analysis. There are numerous content analysis software out there. Don't forget to look at our own content analysis module namedWordStat which is integrated within Simstat, a general statistical software. You can get information on our software from: www.simstat.com and more specifically on the content analysis module from: www.simstat.com/wordstat.htm Normand Peladeau Provalis Research Luis García de la Fuente [EMAIL PROTECTED] wrote in message [EMAIL PROTECTED]">news:[EMAIL PROTECTED]... Hi to all I´m conducting a study around electronic content analysis. Any information / references would be wellcome: links, books, thoughts, etc. My main question / concern is: To what extent is it possible today for computers to generate summaries on articles, books, etc. using neural networks, simple word counting, etc. ? I would enjoy to exchange some thoughts about this issue as well Thanks Luis García de la Fuente = 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: coefficient in logistic regression
Assuming you have coded everything correctly, I would look at something called complete or quasi-complete separation. These conditions often lead to grossly inflated coefficients. Claudiu D. Tufis wrote: Hi, I have a multiple logistic regression. Among the predictors, I have 6 variables that represent the dummies for an interaction term (the seventh is the reference category and is not included in analysis). I have obtained for five of these variables extremely large coefficients: exp(b) ranges from 90,000 to 166,000. Could you please tell me if it is normal to have such values for exp(b)? Do you think it is something wrong? Thank you very much -- Tim Victor Policy Research, Evaluation, and Measurement Psychology in Education Division Graduate School of Education University of Pennsylvania = 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: How to compute Beta variates
Hi ! Thanks a lot for all your help, folks. I solved the problem with all your help. Was surprised to get so much answers. Again, thank you Bye Michael Bals = 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: coefficient in logistic regression
Something from Greenland and Rothman's book Modern Epidemiology (page 258) may apply here: there is a hallmark sysmptom of the bias that arises when stratification has exceeded the limits of the data: The exposure effect estimates begin to get further and further from the null as more variables are added to the stratification or regression model. [...] This inflation is sometimes mistakenly interpreted as evidence of confounding, but in our experience is more often bias due to applying large-sample methods to excessively sparse data. how many variables are in your model? maybe you're stratifying so much that you're ending up with near-empty cells. KH At 10:44 AM 1/26/2002 -0500, Timothy W. Victor wrote: Assuming you have coded everything correctly, I would look at something called complete or quasi-complete separation. These conditions often lead to grossly inflated coefficients. Claudiu D. Tufis wrote: Hi, I have a multiple logistic regression. Among the predictors, I have 6 variables that represent the dummies for an interaction term (the seventh is the reference category and is not included in analysis). I have obtained for five of these variables extremely large coefficients: exp(b) ranges from 90,000 to 166,000. Could you please tell me if it is normal to have such values for exp(b)? Do you think it is something wrong? Thank you very much -- Tim Victor Policy Research, Evaluation, and Measurement Psychology in Education Division Graduate School of Education University of Pennsylvania = 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/ =
DALÍ - JUAN GRIS - PICASSO - MIRÓ
DALÍ - JUAN GRIS - PICASSO - MIRÓ - SOLANA http://www.spanisharts.com/reinasofia/dali.htm = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
Información
A quien corresponda: Necesito información acerca de cómo obtener revisiones (reviews)sobre el aprendizaje y la enseñanza de la estadística. Agradeceré cualquier comentario. Héctor Francisco Reynoso Tirado [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/ =
