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akaike information criterion

27 papers and 2 presentations; 25 titles.

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Conference × Year × Title × Authors Extras Pages
SESUG 2024 A Comprehensive Analysis of the Relationship Between Depression, Sleep Deprivation, and Self-Esteem Using Advanced Statistical Methods Muslihat Adejoke Gaffari source 43
WUSS 2024 Correlation of a Composite Self-Reported Symptoms Severity Score with Patient Number of Symptoms as Predictors of SARS-CoV-2 infection status/Viral Load using the SAS System [presentation] Jesse Albert Canchola,
Daniel Jarem,
Alison Kuchta		 source 54
SESUG 2023 %modelselect: A macro for automatically selecting statistical models based on fit statistics William B. Smith source 7
SESUG 2023 Longitudinal Analysis of Marital Therapy's Impact on Intimacy in Heterosexual Couples Yaa Awuah,
Mostafa Zahed		 source 19
SGF 2020 Using Analytics to Predict Tax Recovery and Prioritize Audits and Investigations in Canada Jason A. Oliver source 19
SGF 2020 Winning Tactics for SAS Visual Data Mining and Machine Learning: Why it's the Only Skill You Need Chris St. Jeor source 12
SGF 2019 IFRS9: Using SAS/ETD Software and SAS Studio to Select Macro Economic Variables Julio Alberto Campa Vega Filho source 19
MWSUG 2018 Application of heavy-tailed distributions using PROC IML, NLMIXED and SEVERITY Palash Sharma 14
PharmaSUG 2018 An Introduction to the Analysis of Rare Events Nathaniel Derby source 19
WUSS 2017 Is My Model the Best? Methods for Exploring Model Fit Deanna Naomi Schreiber-Gregory source 7
SESUG 2016 SAS Macro for Automated Model Selection Involving PROC GLIMMIX and PROC MIXED Fan Pan,
Jin Liu		 source 9
MWSUG 2016 Is My Model the Best? Methods for Exploring Model Fit Deanna Naomi Schreiber-Gregory 7
WUSS 2016 Selection Bias: How Can Propensity Score Utilization Help Control For It? Deanna Naomi Schreiber-Gregory source 13
SGF 2015 The %ic_mixed Macro: A SAS Macro to Produce Sorted Information Criteria (AIC and BIC) List for PROC MIXED for Model Selection Qinlei Huang source 16
MWSUG 2012 Combined Forecasts: What to Do When One Model Isn't Good Enough Ed Blair,
Michael J. Leonard,
Bruce Elsheimer		 14
SGF 2012 Combined Forecasts: What to Do When One Model Isn't Good Enough Ed Blair,
Michael J. Leonard,
Bruce Elsheimer		 source 14
WUSS 2011 An Introduction to the Analysis of Rare Events Nathaniel Derby source 19
MWSUG 2011 An Introduction to the Analysis of Rare Events Nathaniel Derby 19
SGF 2011 Bivariate Count Data Regression Models: A SAS Macro Program Nan-Ting Chou,
David Steenhard		 source 10
MWSUG 2009 Mixed Model Selection George C. J. Fernandez 19
WUSS 2008 User-friendly SAS Macro Application for performing all possible mixed model selection - An update George C. J. Fernandez source 19
SGF 2008 Structural Equation Modeling and Path Analysis Using PROC TCALIS in SAS 9.2 Yiu-Fai Yung source 20
SESUG 2007 Data Mining and Investigating Treatment Options of Osteomyelitis with MRSA Hamed Zahedi source 9
PharmaSUG 2007 Effects of Multicollinearity in All Possible Mixed Model Selection George C. J. Fernandez 18
SGF 2007 Model Selection in PROC MIXED-A User-Friendly SAS Macro Application George C. J. Fernandez source 20
MWSUG 2006 All Possible Model Selection in Proc Mixed - A SAS macro application George C. J. Fernandez 19
WUSS 2006 Model Selection Methods in PROC MIXED George C. J. Fernandez source 19
NESUG 2000 How to Be a Bayesian in SAS: Model Selection Uncertainty in PROC LOGISTIC and PROC GENMOD Ernest S. Shtatland 9
SEUGI 1996 An automated sales forecasting system [presentation] UNKNOWN source 67

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