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181	Removing the Scale Factor Confound in Multinomial Logit Choice Models to Obtain Better Estimates of Preference1 Jay Magidson Statistical Innovations Inc. Jeroen K. Vermunt Add to Reading List Source URL: statisticalinnovations.com Language: English - Date: 2008-09-23 15:42:55 Categorical data Statistical models Choice modelling Scientific modeling Discrete choice Logistic regression Multinomial logit Scale parameter Parameter Statistics Economics Regression analysis
182	YALE JOURNAL OF BIOLOGY AND MEDICINE), pp. x-x. Copyright © 2002. All rights reserved. ORIGINAL CONTRIBUTION GOLDmineR: Improving Models for Add to Reading List Source URL: statisticalinnovations.com Language: English - Date: 2006-09-05 12:13:50 Categorical data Medical statistics Epidemiology Logistic regression Odds ratio Odds Logit Linear regression Level of measurement Statistics Regression analysis Econometrics
183	www.nr.no Generalized linear models in R Magne Aldrin, Norwegian Computing Center and the University of Oslo Sharp workshop, Copenhagen, October 2012 Add to Reading List Source URL: www.nrcse.washington.edu Language: English - Date: 2012-10-17 18:02:34 Statistical models Categorical data Actuarial science Generalized linear model Linear regression Logit Logistic regression Poisson regression Linear model Statistics Regression analysis Econometrics
184	Generalized linear and additive models Exercise 1 Precipitation data from Tryvann, Oslo We will use the mgcv package. If you have not installed it yet; install it now. Load it into R by require(mgcv) or library(mgcv). Co Add to Reading List Source URL: www.nrcse.washington.edu Language: English - Date: 2012-10-17 18:03:39 Logistic regression Generalized additive model Logit Nonparametric regression Statistics Regression analysis Additive model
185	Active Learning for Logistic Regression Andrew I. Schein The University of Pennsylvania Department of Computer and Information Science Philadelphia, PAUSA Add to Reading List Source URL: www.andrewschein.com Language: English - Date: 2011-08-13 15:18:52 Machine learning Logistic regression Multinomial logit Mean squared error Training set Loss function Statistical classification Supervised learning Book:Machine Learning - The Complete Guide Statistics Econometrics Regression analysis
186	Microsoft Word - IJMEDMarch2010 Add to Reading List Source URL: risk.earthmind.net Language: English - Date: 2012-10-11 10:47:44 Decision theory Regression analysis Statistical models Actuarial science Utility Discrete choice Choice modelling Multinomial logit Choice set Economics Statistics Knowledge
187	An Extension of the CHAID Tree-based Segmentation Algorithm to Multiple Dependent Variables Jay Magidson1 and Jeroen K. Vermunt2 1 2 Add to Reading List Source URL: statisticalinnovations.com Language: English - Date: 2009-01-30 12:07:07 Econometrics Categorical data Psychometrics CHAID Latent class model Multinomial logit Decision tree learning Latent variable Factor analysis Statistics Regression analysis Decision trees
188	latent gold 4.0 manual final for pdf.qxp Add to Reading List Source URL: statisticalinnovations.com Language: English - Date: 2005-04-29 16:37:52 Statistical models Psychometrics Categorical data Latent class model Latent variable model Structural equation modeling Logistic regression Linear regression Multinomial logit Statistics Regression analysis Econometrics
189	Mining for Gold gets easier and a lot more fun! By Ken Deal Marketing researchers develop and use scales routinely. It seems to be a fairly common procedure when analyzing survey data to assume that a seemingly well-deve Add to Reading List Source URL: statisticalinnovations.com Language: English - Date: 2006-09-05 12:48:21 Linear regression Logistic regression Multinomial logit SPSS Dummy variable Data transformation Statistics Regression analysis Econometrics
190	Title stata.com glm — Generalized linear models Syntax Add to Reading List Source URL: www.stata.com Language: English - Date: 2014-12-10 18:57:08 Econometrics Actuarial science Model selection Generalized linear model Poisson regression Binomial regression Logit Deviance Bayesian information criterion Statistics Regression analysis Categorical data

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