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Bruce S. Lund

32 papers; 31 titles; 5 coauthors.

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Conference × Year × Title × Co-authors Extras Pages
SESUG 2023 Binning Predictors for Logistic Regression source 25
SESUG 2021 Screening, Binning, Transforming Predictors for a Generalized Logit Model source 17
SGF 2021 Weight of Evidence, Dummy Variables and Degrees of Freedom source
sas
presentation
pdf		 15
MWSUG 2019 Logistic Regression, Basics and Beyond 35
SGF 2019 Screening, Transforming, and Fitting Predictors for the Cumulative Logit Model source 21
SGF 2019 Transforming Ordinal Predictors to Numeric For Binary Logistic Models source 10
MWSUG 2018 Propensity Scores and Causal Inference for (and by) a Beginner 18
MWSUG 2018 Screening, Transforming, and Fitting Predictors for Cumulative Logit Model 22
SGF 2018 The Function Selection Procedure source 11
SESUG 2017 Binning of Predictors for the Cumulative Logit Model source 20
MWSUG 2017 Logistic Model Selection with SAS PROC's LOGISTIC, HPLOGISTIC, HPGENSELECT 18
SGF 2017 SAS Macros for Binning Predictors with a Binary Target source 13
SGF 2017 Weight of Evidence Coding for the Cumulative Logit Model source 15
MWSUG 2016 The Practice of Credit Risk Modeling for Alternative Lending Keith Shields 8
MWSUG 2016 Weight of Evidence Coding and Binning of Predictors in Logistic Regression 16
SGF 2016 Finding and Evaluating Multiple Candidate Models for Logistic Regression source
zip		 17
SGF 2016 Probability Density for Repeated Events source 16
MWSUG 2015 Fitting and Evaluating Logistic Regression Models 26
SESUG 2015 Probability Density for Repeated Events source 16
SGF 2015 Multinomial Logistic Model for Long-Term Value source 16
SGF 2015 Selection and Transformation of Continuous Predictors for Logistic Regression source 16
SCSUG 2014 Selection and Transformation of Continuous Predictors for Logistic Regression 13
MWSUG 2014 Preparing Interaction Variables for Logistic Regression 9
MWSUG 2014 Selection and Transformation of Continuous Predictors for Logistic Regression 12
SCSUG 2013 Preparing Interaction Variables for Logistic Regression source 14
MWSUG 2013 Information Value Statistic David Brotherton 18
SGF 2013 A Flock of C-Stats, or Efficiently Computing Multiple Statistics for Hundreds of Variables Steven Raimi source 11
NESUG 2012 Efficiently Screening Predictor Variables for Logistic Models Steven Raimi 13
MWSUG 2012 Collapsing Levels of Predictor Variables for Logistic Regression and Weight of Evidence Coding Steven Raimi 13
MWSUG 2012 Direct Marketing Profit Model 8
MWSUG 2011 Before Logistic Modeling - A Toolkit for Identifying and Transforming Relevant Predictors Steven Raimi 18
MWSUG 2008 Long-Term Value Modeling in the Automobile Industry Jeff Ames,
Cathy Hackett		 6

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