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backward selection

45 papers; 43 titles.

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Conference × Year × Title × Authors Extras Pages
PharmaSUG 2024 Multiple Logistic Regression Analysis using Backward Selection Process on Objective Response Data with SAS Girish Kankipati,
Jai Deep Mittapalli		 source 9
SGF 2020 A Survey of Methods in Variable Selection and Penalized Regression Yingwei Wang source 17
WUSS 2019 A strategy for speed Dating YuTing Tian source 21
SGF 2019 Machine Learning and Predictive Analytics in SAS Enterprise Miner and SAS/STAT Software David Richard Cutler source 21
SCSUG 2018 Backward Elimination in Firth's penalized partial likelihood Approach: Firth's Logistic and Cox Models Chao Zhang source 7
WUSS 2018 Combined Predictor Selection for Multiple Clinical Outcomes Using PHREG L. Grisell Diaz-Ramirez,
Siqi Gan,
Sei J. Lee,
Alexander Smith,
John Boscardin		 source 14
SGF 2018 Demystify Income Models with Advanced Machine Learning Techniques for Ultimate Accuracy Vickey Chang source 18
PHUSE EU 2017 The Model Statistician Insights into Model Selection Techniques in Clinical Trials Peter Williams source
presentation source		 6
SGF 2017 Interrupted Time Series Power Calculation using DO Loop Simulations Nigel Rozario,
Andrew McWilliams,
Charity Moore		 source 15
SGF 2017 What Statisticians Should Know about Machine Learning David Richard Cutler source 13
SESUG 2016 Statistical Model Building for Large, Complex Data: Five New Directions in SAS/STAT Software Robert N. Rodriguez source 23
SESUG 2016 Using JMP to apply Decision Trees and Random Forests as Screening Tools for Limiting Candidate Predictors in Regression Models Jason Brinkley source 10
MWSUG 2016 An Analysis of the Repetitiveness of Lyrics in Predicting a Song's Popularity Drew Doyle 12
MWSUG 2016 Regression Analysis of the Levels of Chlorine in the Public Water Supply in Orange County, FL Drew Doyle 11
WUSS 2016 Statistical Model Building for Large, Complex Data: Four New Directions in SAS/STAT Software Robert N. Rodriguez source 23
SGF 2016 Comparative Regional Analysis of Bacterial Pneumonia Readmission Patients in the Medicare Category Heramb Joshi,
Goutam Chakraborty,
William Paiva,
Aditya Sharma		 source 12
SGF 2016 Statistical Model Building for Large, Complex Data: Five New Directions in SAS/STAT Software Bob Rodriguez source 23
SESUG 2015 Regression Analysis of the Levels of Chlorine in the Public Water Supply in Orange County, FL Drew Doyle source 10
SGF 2015 Using SAS to Combine Regression and Time Series Analysis on U.S. Financial Data to Predict the Economic Downturn Avinash Kalwani,
Nishant Vyas		 source 6
PHUSE EU 2014 Backward Selection: Immunity Test of Covariates Prathamesh Athavale source
presentation source		 10
MWSUG 2014 A SAS Macro Using Parallel Genetic Algorithm to Automate Variable Selection Jinqiao Li,
Yi Cao,
Yanping Shen		 19
MWSUG 2014 Measuring Product-level Promotional Effectiveness using Multiple Linear Regression Aaron Clark,
Cory Weinmann,
Donald Kirk		 10
WUSS 2013 An Algorithm for ARIMA Dynamic Regression Variable Selection Ross Bettinger source 14
SESUG 2013 Introducing the New ADAPTIVEREG Procedure for Adaptive Regression Warren F,
Weijie Cai		 source 21
SGF 2013 Regression of NASCAR: Looking into Five Years of Jimmie Johnson Alex Herrington,
Liuchun Yang,
Yun Gao		 source 20
PharmaSUG 2012 Automated forward selection for Generalized Linear Models with Categorical and Numerical Variables using PROC GENMOD Manuel Sandoval source 5
SGF 2012 Including the Salesperson Effect in Purchasing Behavior Models Using PROC GLIMMIX Philippe Baecke,
Dirk Van den Poel		 source 11
MWSUG 2011 SAS Model Selection Macros for Complex Survey Data Using PROC SURVEYLOGISTIC/SURVEYREG Fang Wang,
Hee-Choon Shin		 27
MWSUG 2011 Using SAS to Create Sales Expectations for Everyday and Seasonal Products Lory Ellebracht,
Jamie Netherton,
Casey Gentry		 10
SESUG 2009 A Logistic Regression Model to Predict Freshmen Enrollments Vijayalakshmi Sampath,
Andrew Flagel		 source 12
SESUG 2009 Developing Business Failure Prediction Models Using SAS Software Oki Kim source 10
WUSS 2009 Developing Business Failure Prediction Models Using SAS Software Oki Kim source 10
WUSS 2009 Discriminant Analysis, a Powerful Classification Technique in Predictive Modeling George C. J. Fernandez source 20
NESUG 2007 Using Macro and ODS to Overcome Limitations of SAS Procedures Wei (Lisa) Lin,
Jing Su		 7
SESUG 2007 Information Criteria Methods in SAS for Multiple Linear Regression Models Dennis J. Beal source 10
SCSUG 2007 A SAS Macro for Hosmer and Lemeshow's Purposeful Selection Model Building Algorithm: Description and Performance David Williams,
Zoran Bursac,
David K. Hosmer		 6
SGF 2007 A Purposeful Selection of Variables Macro for Logistic Regression Zoran Gauss,
C. Heath Williams,
David K. Hosmer,
David W. Bursac		 source 5
MWSUG 2006 A SAS Macro for Performing Backward Selection in Proc Surveyreg Qixuan Chen 5
SESUG 2005 SAS Code to Select the Best Multiple Linear Regression Model for Multivariate Data Using Information Criteria Dennis J. Beal,
Oak Ridge		 source 6
WUSS 2003 Logistic regression model-building strategies for predicting regular mammography screening adherence among uninsured immigrant women Jesse Albert Canchola,
Regina Otero-Sabogal,
Desiree Owens,
Farzaneh Tabnak		 source 6
NESUG 2002 Integration of SAS and NONMEM for Automation of Population Pharmacokinetic/Pharmacodynamic Modeling on UNIX systems Alan Xiao,
Jill Fiedler-Kelly		 5
SUGI 2002 Automating the Building of 2nd and 3rd Order Interactions and the Construction of Hierarchical Logistic Regression Models Mazen Abdellatif,
Robert G. Anderson,
Domenic J. Reda		 source 4
SCSUG 2001 Ideas on Variable Selection and Alternative Links in Procedure CATMOD Kimberly DeJarnatt,
James E. Dunn		 4
SESUG 1996 Stepwise Regression as a Multiple Comparison Procedure Rodney Sparapani 3
SEUGI 1993 Variable Selection Techniques Implemented in Procedures of SAS Software Olaf Gefeller source 9

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