<html><head><style type='text/css'>p { margin: 0; }</style></head><body><div style='font-family: times new roman,new york,times,serif; font-size: 12pt; color: #000000'> <BLOCKQUOTE style="FONT-SIZE: 12pt; TEXT-DECORATION: none; FONT-FAMILY: Helvetica,Arial,sans-serif; FONT-WEIGHT: normal; COLOR: #000; FONT-STYLE: normal; PADDING-LEFT: 5px; MARGIN-LEFT: 5px; BORDER-LEFT: rgb(16,16,255) 2px solid"> <STYLE>p { margin: 0; }</STYLE> <DIV style="FONT-SIZE: 12pt; FONT-FAMILY: times new roman,new york,times,serif; COLOR: #000000"> <BLOCKQUOTE style="FONT-SIZE: 12pt; TEXT-DECORATION: none; FONT-FAMILY: Helvetica,Arial,sans-serif; FONT-WEIGHT: normal; COLOR: #000; FONT-STYLE: normal; PADDING-LEFT: 5px; MARGIN-LEFT: 5px; BORDER-LEFT: rgb(16,16,255) 2px solid"> <DIV dir=ltr> <DIV> <DIV style="FONT-SIZE: 12pt; FONT-FAMILY: times new roman,new york,times,serif; COLOR: #000000">Caros colegas, Seguem informações sobre o Workshop on Categorical Data Analysis, por Alan Agresti, 08 a 10/03/2016, das 9 às 11h e das 14 às 16h. Número limitado de vagas. Inscrições abertas: <A href="http://fealq.org.br/informacoes-do-evento/?id=371" target=_blank>http://fealq.org.br/informacoes-do-evento/?id=371</A> Saudações, Clarice ####################################### Categorical Data Analysis (Three-day course, with 4 hours lecturing each day, following the book "Categorical Data Analysis," 3rd ed., by Alan Agresti) Abstract This short course surveys the most common methods for analyzing categorical data. The first part of the course focuses on contingency table analysis, logistic regression modeling of binary data, and loglinear models. The second part introduces logistic models for multi-category ordinal and nominal responses and for clustered data using generalized estimating equations (GEE) and random effects. The presentation emphasizes interpretation rather than technical details, with examples including social surveys and randomized clinical trials. Examples show the use of R and SAS. Outline timetable (tentative) Day 1 Contingency tables, odds ratios, chi-squared tests, Fisher's exact test, logistic regression as a generalized linear model, interpretations, inference using logistic regression Day 2 Logistic regression model building, detecting infinite logistic estimates (with remedies), introduction to loglinear models Cochran-Mantel-Haenszel test, sample size and power, baseline-category logit model for nominal data Day 3 Cumulative logit model for ordinal data, analyzing correlated categorical data, GEE for marginal models, random effects models Agresti: Short CV Alan Agresti is Distinguished Professor Emeritus, Department of Statistics, University of Florida. The past seven years he was also visiting professor for half the year at Harvard University. He has written seven books and more than 200 research articles. His book `Categorical Data Analysis' (3rd edition, 2013) has received nearly 20,000 citations in journal articles. Other books include `Analysis of Ordinal Categorical Data' (2nd edition, 2010), `Foundations of Linear and Generalized Linear Models' (2015), `Statistical Methods for the Social Sciences' (5th edition, 2016), and `Statistics: The Art and Science of Learning from Data' (4th edition 2016). He received an Honorary Doctor of Science from De Montfort University in 1999, the Statistician of the Year Award from the Chicago chapter of the American Statistical Association in 2003, and the first Herman Callaert Leadership Award in Biostatistical Education and Dissemination from Hasselt University, Belgium in 2004. He has been awarded Fellow designation by both the American Statistical Association and the Institute of Mathematical Statistics. He has lectured on categorical data methods in more than 30 countries. For further details, see <A href="http://www.stat.ufl.edu/~aa" target=_blank>www.stat.ufl.edu/~aa</A>. </DIV> _______________________________________________ abe mailing list abe@lists.ime.usp.br https://lists.ime.usp.br/mailman/listinfo/abe</DIV></DIV></BLOCKQUOTE> </DIV></BLOCKQUOTE> </div></body></html>