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Peter L. Flom

25 papers; 22 titles; 7 coauthors.

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Conference × Year × Title × Co-authors Extras Pages
SGF 2020 You Are Using PROC GLM Too Much (and What You Should Be Using Instead) source 22
PharmaSUG 2020 You Are Using PROC GLM Too Much (and What You Should Be Using Instead) Deanna Naomi Schreiber-Gregory source 15
SESUG 2019 Graphics for Univariate Data: Pie is Delicious But Not Nutritious source 11
SESUG 2019 Scatterplots: Basics, Enhancements, Problems, and Solutions source 13
MWSUG 2019 Scatterplots: Basics, Enhancements, Problems, and Solutions 13
MWSUG 2018 Alternative Methods of Regression when OLS is Not Right 22
MWSUG 2018 An introduction to classification and regression trees with PROC HPSPLIT. 13
SESUG 2016 PROC LOGISTIC: Traps for the unwary source 7
SESUG 2015 Alternative Methods of Regression when OLS is Not Right source 28
WUSS 2015 Introduction to SAS Quantile Regression (PROC QuantSelect and PROC QuantReg ) source 25
SGF 2015 Alternative Methods of Regression when OLS is Not Right source 19
SGF 2015 Preparing Output from Statistical Procedures for Publication, Part 1: PROC REG to APA Format Vincent DelGobbo source 27
MWSUG 2014 Should more of your PROC REGS be QUANTREGs and ROBUSTREGs? 17
SGF 2014 Scatterplots: Basics, Enhancements, Problems, and Solutions source 13
NESUG 2012 Graphics for Univariate Data: Pie is Delicious But Not Nutritious 11
SESUG 2011 Scatterplots: Basics, Enhancements, Problems, and Solutions source 12
NESUG 2011 Quantile Regression with PROC QUANTREG 9
NESUG 2011 Using the SG Procedures to create and enhance scatter plots 12
NESUG 2010 Multinomial and ordinal logistic regression using SAS 12
NESUG 2010 Super Simple Macros to Make a Statistician's Life Simpler 5
SGF 2010 Building a Decision Tree from Decision Stumps Murphy Choy source 7
NESUG 2009 Stopping Stepwise: Why Stepwise Selection Methods are Bad and What you Should use Instead David L. Cassell 7
NESUG 2008 PROC LOGISTIC: Traps for the unwary 8
NESUG 2006 Using PROC NLMIXED and PROC GLIMMIX to analyze dyadic data with binary outcomes Samuel Friedman,
James McMahon,
Enrique Pouget		 10
NESUG 2005 Logistic Regression: Ordinal and Nominal Outcomes 9

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