Books on the topic 'Bayesian logistic regression models'

Houston, Walter M. Empirical Bayes estimates of parameters from the logistic regression model. Iowa City, Iowa: ACT, Inc., 1997.

Houston, Walter M. Empirical Bayes estimates of parameters from the logistic regression model. Iowa City, Iowa: ACT, Inc., 1997.

Hilbe, Joseph. Logistic regression models. Boca Raton: Chapman & Hall/CRC, 2009.

Ronald, Christensen. Log-linear models and logistic regression. 2nd ed. New York: Springer, 1997.

O'Connell, Ann. Logistic Regression Models for Ordinal Response Variables. 2455 Teller Road, Thousand Oaks California 91320 United States of America: SAGE Publications, Inc., 2006. http://dx.doi.org/10.4135/9781412984812.

Regression modeling strategies: With applications to linear models, logistic regression, and survival analysis. New York: Springer, 2001.

Guttman, Irwin. Bayesian assessment of assumptions of regression analysis. Toronto: University of Toronto, Dept. of Statistics, 1988.

Bagchi, Parthasarathy. Bayesian assessment of assumptions of regression analysis. Toronto: University of Toronto, Dept. of Statistics, 1989.

Pilz, Jürgen. Bayesian estimation and experimental design in linear regression models. Chichester: Wiley, 1991.

Pilz, Jürgen. Bayesian estimation and experimental design in linear regression models. 2nd ed. Chichester: Wiley, 1991.

Spray, Judith A. Comparison of loglinear and logistic regression models for detecting changes in proportions. Iowa City: American College Testing Program, 1988.

Murphy, Karl. Nested Analysis: Identifying and Applying Qualitative Illustration Support for Logistic Regression Models. 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications, Ltd., 2019. http://dx.doi.org/10.4135/9781526496478.

Allison, Paul David. Logistic regression using the SAS system: Theory and application. Cary, N.C: SAS Institute, 1999.

Bent, Gardner C. A logistic regression equation for estimating the probability of a stream flowing perennially in Massachusetts. Northborough, Mass: U.S. Dept. of the Interior, U.S. Geological Survey, 2002.

Bent, Gardner C. A logistic regression equation for estimating the probability of a stream flowing perennially in Massachusetts. Northborough, Mass: U.S. Dept. of the Interior, U.S. Geological Survey, 2002.

Bent, Gardner C. A logistic regression equation for estimating the probability of a stream flowing perennially in Massachusetts. Northborough, Mass: U.S. Dept. of the Interior, U.S. Geological Survey, 2002.

Bent, Gardner C. A logistic regression equation for estimating the probability of a stream flowing perennially in Massachusetts. Northborough, MA (10 Bearfoot Rd., Northborough 01532): U.S. Department of the Interior, U.S. Geological Survey, 2002.

Guttman, Irwin. Bayesian method of detecting change point in regression and growth curve models. Toronto: University of Toronto, Dept. of Statistics, 1985.

Neal, Radford M. Monte Carlo implementation of Gaussian process models for Bayesian regression and classification. Toronto: University of Toronto, 1997.

Press, S. James. Bayesian statistics: Principles, models, and applications. New York: Wiley, 1989.

K, Neerchal Nagaraj, and SAS Institute, eds. Overdispersion models in SAS. Cary, N.C: SAS Institute, 2012.

Gelman, Andrew. Regression and Other Stories. Cambridge, UK: Cambridge University Press, 2020.

Loftsgaarden, Don O. Constructing and testing logistic regression models for binary data: Applications to the national fire danger rating system. Ogden, Utah: U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1992.

Loftsgaarden, Don O. Constructing and testing logistic regression models for binary data: Applications to the National Fire Danger Rating System. Ogden, UT (324 25th St., Ogden 84401): U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1992.

Kery, Marc. Introduction to WinBUGS for ecologists: Bayesian approach to regression, ANOVA, mixed models and related analyses. Amsterdam: Elsevier, 2010.

Lemeshow, Stanley. Applied Survival Analysis: Regression Modeling of Time to Event Data. 2nd ed. Hoboken, N.J: Wiley-Interscience, 2008.

Kéry, Marc. Introduction to WinBUGS for ecologists: A Bayesian approach to regression, ANOVA, mixed models and related analyses. Amsterdam: Elsevier, 2010.

Kennedy, R. Lee. A comparison of logistic regression and artificial neural network models for the early diagnosis of acute myocardialinfarction (AMI). Sheffield: University of Sheffield, Dept. of Automatic Control & Systems Engineering, 1994.

Guttman, Irwin. Estimating the number of aberrant laboratories. Toronto, Ont: University of Toronto, Dept. of Statistics, 1993.

Bulinski, Alexander, ed. Encyclopaedia of Applied Statistics: Using SPSS, Statistica and Matlab: Using SPSS, Statistica and Matlab (3 Volumes). USA: Koros Press Limited, 2015.

Data analysis and approximate models: Model choice, location-scale, analysis of variance, nonparametic regression and image analysis. Boca Raton: CRC Press, 2014.

Tu, Jack Ven. A comparison of neural network and logistic regression models for predicting length of stay in the intensive care unit following cardiac surgery. Ottawa: National Library of Canada = Bibliothèque nationale du Canada, 1993.

Hosmer, David W. Applied survival analysis: Regression modeling of time-to-event data. 2nd ed. Hoboken, N.J: John Wiley & Sons, 2008.

Hosmer, David W. Applied survival analysis: Regression modeling of time-to-event data. 2nd ed. Hoboken, N.J: Wiley-Interscience, 2008.

Stanley, Lemeshow, ed. Applied survival analysis: Regression modeling of time to event data. New York: Wiley, 1999.

Hilbe, Joseph M. Logistic Regression Models. Taylor & Francis Group, 2009.

Hilbe, Joseph M. Logistic Regression Models. Chapman and Hall/CRC, 2009. http://dx.doi.org/10.1201/9781420075779.

Logistic Regression Models. Chapman & Hall/CRC, 2009.

Christensen, Ronald. Log-Linear Models and Logistic Regression. Springer, 2013.

Log-Linear Models and Logistic Regression. New York: Springer-Verlag, 1997. http://dx.doi.org/10.1007/b97647.

Sjamsoe'oed, Roza. The use of logistic regression for developing habitat association models. 1994.

Regression Methods In Biostatistics Linear Logistic Survival And Repeated Measures Models. Springer, 2011.

Eric, Vittinghoff, ed. Regression methods in biostatistics: Linear, logistic, survival, and repeated measures models. New York: Springer, 2005.

Vittinghoff, Eric, David V. Glidden, and Stephen C. Shiboski. Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models. Springer, 2012.

McCulloch, Charles E., Eric Vittinghoff, David V. Glidden, and Stephen C. Shiboski. Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models. Springer, 2014.

Regression Modeling Strategies: With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis. Springer, 2015.

Rice, Daniel M. Calculus of Thought: Neuromorphic Logistic Regression in Cognitive Machines. Elsevier Science & Technology Books, 2013.

Introduction to Regression Modeling (with CD-ROM) (Duxbury Applied). Duxbury Press, 2005.

Logistic Regression Models for Ordinal Response Variables (Quantitative Applications in the Social Sciences). Sage Publications, Inc, 2005.

McCulloch, Charles E., Eric Vittinghoff, David V. Glidden, and Stephen C. Shiboski. Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models (Statistics for Biology and Health). Springer, 2007.