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latent variable

69 papers; 67 titles.

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Conference × Year × Title × Authors Extras Pages
PharmaSUG 2024 Bayesian Models with the Power Prior Using PROC BGLIMM Yi Gong,
Fang K. Chen		 source 15
SESUG 2022 Embracing Cross-Loading to Improve Latent Variable Models Fit: A comparison of available options in SAS, Mplus, and R Kevin B. Gittner,
Niloofar Ramezani,
Katherine Mobley		 source 26
SGF 2019 Analyzing Structural Causal Models using the CALIS Procedure Banoo Madhanagopal,
John Amrhein		 source 23
SGF 2019 Causal Analyses Using Structural Equation Models Banoo Madhanagopal,
John Amrhein		 source 23
WUSS 2018 A latent variable location scale model for intensive longitudinal data Shelley A. Blozis source 3
SGF 2018 Bayesian Networks for Causal Analysis John Amrhein,
Fei Wang		 source 11
SGF 2018 Confirmatory Factor Analysis in SAS : Application to Public Administration Niloofar Ramezani source 13
SGF 2018 Development of an Individual-Level Social Determinants of Health (SDoH) Classification Model Ryan C. Butterfield,
Paul A. LaBrec		 source 13
SGF 2018 Factors versus Clusters Diana D. Suhr source 16
WUSS 2016 Employing Latent Analyses in Longitudinal Studies: An Exploration of Independently Developed SAS Procedures Deanna Naomi Schreiber-Gregory source 14
PharmaSUG 2016 Latent Structure Analysis Procedures in SAS Deanna Naomi Schreiber-Gregory source 8
SGF 2016 Latent Structure Analysis Procedures in SAS Deanna Naomi Schreiber-Gregory source 8
SGF 2016 Multiple-Group Multiple Imputation: An Empirical Comparison of Parameter Recovery in the Presence of Missing Data using SAS Patricia Rodríguez de Gil,
Jeffrey D. Kromrey		 source 15
SGF 2016 Using SAS to Conduct Multivariate Statistical Analysis in Educational Research: Exploratory Factor Analysis and Confirmatory Factor Analysis Jun Xu,
Steven L. Holtzman,
Kevin Petway,
Lili Yao		 source 13
SGF 2016 Using SAS to Implement Simultaneous Linking in Item Response Theory Lili Yao source 6
SESUG 2015 How Latent Structure Analysis Can Improve the Fit of a Regression Model Deanna Naomi Schreiber-Gregory source 11
WUSS 2015 Latent Analysis Applications for Regression Models Deanna Naomi Schreiber-Gregory source 11
PharmaSUG 2015 How To Use Latent Analyses Within Survey Data Can Be Valuable Additions to Any Regression Model Deanna Naomi Schreiber-Gregory source 9
SGF 2015 How Latent Analyses within Survey Data Can Be Valuable Additions to Any Regression Model Deanna Naomi Schreiber-Gregory source 9
MWSUG 2014 Common Method Variance Techniques Bradford R. Eichhorn 11
MWSUG 2014 How To Use Latent Analyses of Survey Data in a Logistic Regression Model Deanna Naomi Schreiber-Gregory 9
SGF 2014 Case-Level Residual Analysis in the CALIS Procedure Catherine Truxillo source 17
SGF 2014 Confirmatory Factor Analysis and Structural Equation Modeling of Non-cognitive Assessments Using PROC CALIS Steven L. Holtzman source 11
WUSS 2013 %CS: A SAS Macro to Calculate and Construct Composite Scores for Large Data Qinlei Huang source 6
SESUG 2013 Using Predetermined Factor Structures to Simulate a Variety of Data Conditions Kevin Coughlin,
Fort Myers		 source 12
PHUSE EU 2013 Around the World in Three Statistical Models: Determing the Level of Measurement Invariance Across Countries of a PRO Instrument Dirk Heerwegh source
presentation source		 29
SCSUG 2012 An analysis of customer preference of automobile products using SAS. Akkarapol Sa-ngasoongsor source 10
WUSS 2012 Exploratory Factor Analysis with the World Values Survey Diana D. Suhr source 19
SGF 2012 Exploratory Factor Analysis with the World Values Survey Diana D. Suhr source 19
SGF 2012 Handling Missing Data by Maximum Likelihood Paul D. Allison source 21
PHUSE EU 2011 An Animated Guide: An Introduction to Latent Class Clustering in SAS Russell M. Lavery source 19
MWSUG 2011 Introducing SAS Structural Equation Modeling for JMP: A New User Interface That Brings the Power of SAS/STAT Software to JMP Software Wayne E. Watson 18
NESUG 2011 An Animated Guide: An Introduction to Latent Class Clustering in SAS Russell M. Lavery 16
NESUG 2011 Confirmatory Factor Analysis and Structural Ehuation Modeling of Non-cognitive Assessments Using PROC CALIS Steven L. Holtzman,
Sailesh Vezzu		 9
SGF 2011 Introducing SAS Structural Equation Modeling: A New User Interface That Brings the Power of SAS/STAT Software to JMP Software Wayne E. Watson source 18
SGF 2011 Logit Models in Practice: B, C, E, G, M, N, O, ... Joseph C. Gardiner,
Zhehui Luo		 source 20
SGF 2011 PATH and LISMOD Languages in SAS PROC TCALIS for Multigroup Comparisons Fei Gu,
Wei Wu		 source 10
WUSS 2010 Answering Your Research Questions with Inferential Statistics Diana D. Suhr source 10
SGF 2010 Building Latent Growth Models Using PROC CALIS: A Structural Equation Modeling Approach Teck Kiang Tan,
Trivina Kang,
David Hogan		 source 19
WUSS 2009 A Biometric Analysis of Twin Data Using PROC MIXED Mo Zheng source 8
WUSS 2009 Guidelines for Reliability, Confirmatory and Exploratory Factor Analysis Diana D. Suhr,
Mary Shay		 source 15
WUSS 2008 Step your way through Path Analysis Diana D. Suhr source 10
SESUG 2008 Marketing Mix Modeling: Techniques and Challenges Patralekha Bhattacharya source 6
SGF 2008 Structural Equation Modeling and Path Analysis Using PROC TCALIS in SAS 9.2 Yiu-Fai Yung source 20
NESUG 2007 EZLID: A SAS Macro for Local Item Dependence Assessment Yung-Chen Hsu,
Tsung-hsun Tsai		 10
SGF 2007 Latent Class Analysis in SAS-Promise, Problems, and Programming David M. Thompson source 12
WUSS 2006 The Basics of Structural Equation Modeling Diana D. Suhr source 19
SUGI 2006 Exploratory or Confirmatory Factor Analysis? Diana D. Suhr source 17
SUGI 2006 Performing Latent Class Analysis Using the CATMOD Procedure David M. Thompson source 8
WUSS 2005 Principal Component Analysis vs. Exploratory Factor Analysis Diana D. Suhr source 10
SUGI 2005 IRT-FIT: SAS Macros for Fitting Item Response Theory (IRT) Models Robert Terry,
Sung-Hyuck Lee		 source 9
SUGI 2005 Principal Component Analysis versus Exploratory Factor Analysis Diana D. Suhr source 11
SUGI 2005 Structured Neural Network Techniques for Modeling Loyalty and Profitability Carl Lee,
Tim Rey,
James W. Mentele,
Michael Garver		 source 13
WUSS 2003 Answering Your Questions with Statistics Diana D. Suhr source 6
SUGI 2003 Reliability, Exploratory and Confirmatory Factor Analysis for the Scale of Athletic Priorities Diana D. Suhr source 7
WUSS 2002 Reliability, Exploratory, & Confirmatory Factor Analysis for the Scale of Atheletic Priorities Diana D. Suhr source 8
WUSS 2002 Structural Equation Modeling: Easy Solutions Using SAS Shuqiang Zhang source 5
SUGI 2002 SEM for Health, Business, and Education Diana D. Suhr source 8
WUSS 2001 PROC GLM or PROC CALIS? Diana D. Suhr source 5
SUGI 2001 PROC GLM or PROC CALIS? Diana D. Suhr source 3
SESUG 2000 Underlying Construct Analysis (UCA): Where Individual Systems End and Human Systems Begin Alvin L. Killough source 8
WUSS 2000 An Overview of remedial tools for collinearity in SAS Chong Ho Yu source 6
WUSS 2000 PROC CALIS Multi-Sample Analysis Diana D. Suhr source 3
WUSS 1999 Application of Threshold Models to the Detection of IgG and IgM Antibodies Louis Munyakazi source 4
WUSS 1998 Which Path with PROC CALIS? Diana D. Suhr source 7
WUSS 1997 Confirmatory Factor Analysis Using PROC CALIS Diana D. Suhr,
James Keaton,
Lynne Kelly,
Cynthia Finch		 source 5
SUGI 1996 Latent-Variable, Structural-Equation Modeling with PROC CALIS Larry Hatcher source 10
SUGI 1995 An Introduction to Partial Least Squares Regression Randall D. Tobias source 8
SUGI 1982 PROC TETCORR: Correlations between Categorical and Continuous Variables. J. Philip Miller,
Michael A. Province,
Reimut Wette		 source 4

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