Joseph Hilbe

Joseph HilbeJoseph M. Hilbe is an emeritus professor at the University of Hawaii, an adjunct professor of statistics at Arizona State University, and a Solar System Ambassador with NASA/Jet Propulsion Laboratory, Caltech. An elected Fellow of the American Statisical Association and elected member of the International Statistical Institute, Dr. Hilbe is currently President of the International Astrostatistics Association, is a full member of the American Astronomical Society, and Chairs the Statistics in Sports section of the American Statistical Association (ASA). He has authored fifteen books in statistical modeling, and over 200 book chapters, encyclopedia entries, journal articles, and published statistical software, and is currently on the editorial board of seven academic journals. During the 1990's Dr Hilbe was on the founding executive committee of the ASA Section on Health Policy Statistics, and served in various capacities in the health research industry, including: CEO of National Health Economics and Research Corp.; Director of Research at Transitional Hospitals Corp, a national chain of long term hospitals; Senior Statistician of NRMI-2, Genentech's National Registry for Myocardial Infarctions; lead biostatistical consultant, Hoffman-La Roche's National Canadian Registry for Cardiovascular Disease; and was Senior Statistical Consultant for HCFA's Medicare Infrastructure Project. Read More Read Less

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Logistic Regression Models (Chapman & Hall/CRC Texts in Statistical Science) [Special Indian Edition - Reprint Year: 2020]35 %
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Modeling Count Data16 %
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Quasi-Least Squares Regression45 %
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Astrostatistical Challenges for the New Astronomy36 %
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Astrostatistical Challenges for the New Astronomy36 %
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Bayesian Models for Astrophysical Data38 %
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Quasi-Least Squares RegressionNR
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Methods of Statistical Model EstimationNR
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Methods of Statistical Model EstimationNR
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Practical Predictive Analytics and Decisioning Systems for Medicine8 % NR
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Logistic Regression Models1 % NR
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Negative Binomial Regression1 % NR
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Practical Guide to Logistic Regression3 % NR
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Logistic Regression ModelsNR
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Practical Guide to Logistic Regression1 % NR
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Generalized Estimating Equations4 % NR
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Generalized Linear Models and Extensions22 %
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