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f-test

57 papers; 53 titles.

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Conference × Year × Title × Authors Extras Pages
SESUG 2023 Wald Tests in Mixed Models - a Warning David A. Dickey source 20
SGF 2020 A Warning about Wald Tests David A. Dickey source 20
WUSS 2018 "Training Wheels" for learning mixed models YuTing Tian,
Russell M. Lavery		 source 20
MWSUG 2016 Regression Analysis of the Levels of Chlorine in the Public Water Supply in Orange County, FL Drew Doyle 11
SGF 2016 What's the Difference? David A. Dickey source 17
SESUG 2015 ANOVA_Robust: A SAS Macro for Various Robust Approaches to Testing Mean Differences in One-Factor ANOVA Models Thanh V. Pham,
Eun Sook Kim,
Diep T. Nguyen,
Yan Wang,
Jeffrey D. Kromrey,
Yi-Hsin Chen		 source 14
SESUG 2015 Coder ' s Corner source 10
SESUG 2015 Regression Analysis of the Levels of Chlorine in the Public Water Supply in Orange County, FL Drew Doyle source 10
SESUG 2014 Strimmed_t: A SAS Macro for the Symmetric Trimmed t Test Diep T. Nguyen,
Anh P. Kellermann,
Eun Sook Kim		 source 12
SGF 2014 Power and Sample Size for MANOVA and Repeated Measures with the GLMPOWER Procedure John M. Castelloe source 20
SGF 2014 Trimmed_t: A SAS Macro for the Trimmed T-Test Patricia Rodríguez de Gil,
Anh P. Kellermann,
Diep T. Nguyen,
Eun Sook Kim,
Jeffrey D. Kromrey		 source 13
MWSUG 2012 Modeling Complex Survey Data Taylor Lewis 16
WUSS 2012 The Steps to Follow in a Multiple Regression Analysis Theresa H. Ngo source 12
SGF 2012 Introduction to Predictive Modeling with Examples David A. Dickey source 14
PharmaSUG 2011 CONTRAST and ESTIMATE Statements Made Easy: The LSMESTIMATE Statement Kathleen Kiernan,
Randy Tobias,
Phil Gibbs,
Jill Tao		 source 19
SGF 2011 CONTRAST and ESTIMATE Statements Made Easy: The LSMESTIMATE Statement Kathleen Kiernan,
Randy Tobias,
Phil Gibbs,
Jill Tao		 source 19
MWSUG 2010 Novel Use of SAS Software in Industrial and Biomedical Consulting, Research, and Teaching Timothy E. O'Brien 13
MWSUG 2010 PROC MIXED: Underlying Ideas with Examples David A. Dickey 19
SGF 2010 Introducing PROC PLM and Postfitting Analyses in Very General Linear Models Randy Tobias,
Weijie Cai		 source 18
PNWSUG 2008 Applied Aspects of Using Multiple Imputation in Clinical Data Christina Gullion 7
SGF 2008 PROC MIXED: Underlying Ideas with Examples David A. Dickey source 18
SESUG 2007 PROC MIXED: Underlying Ideas with Examples David A. Dickey source 19
SGF 2007 Alternatives for Analysis of Complex Sample Surveys: A Comparison of SAS, SUDAAN, and AM Software Bethany A. Kromrey,
Jeffrey D. Bell-Ellison		 source 10
SUGI 2005 Stationarity Issues in Time Series Models David A. Dickey source 17
NESUG 2004 Perusing, Choosing, and Not Mis-using: Non-parametric vs Parametric tests in SAS Venita DePuy,
Paul Pappas		 5
SESUG 2004 An Overview of Non-parametric Tests in SAS: When, Why, and How Paul A. Pappas,
Venita DePuy		 source 5
SUGI 2004 An Animated Guide: The Logic of Hypothesis Testing and ANOVA Russell M. Lavery source 11
NESUG 2003 An Animated Guide: The Logic of Hypothesis Testing and ANOVA Russell M. Lavery 7
WUSS 2002 A Randomization-Test Wrapper for SAS PROCs Christopher F. Ake,
David L. Cassell		 source 4
SUGI 2002 A Randomization-Test Wrapper for SAS PROCs David L. Cassell source 4
SESUG 2001 A Simulation Study to Compare the Performance of Permutation Tests for Time by Group Interaction in an Unbalanced Repeated-Measures Design, Using Two Permutation Schemes Mark S. Litaker,
Bob Gutin		 source 5
SCSUG 2001 A Simulation Study to Compare the Performance of Permutation Tests for Time by Group Interaction in an Unbalanced Repeated-Measures Design, Using Two Permutation Schemes Mark S. Litaker,
Bernard Gutin		 5
SCSUG 2001 Power and Sample Size Determination for Linear Models John M. Castelloe,
Ralph G. O'Brien		 13
SUGI 2001 Probabilistic Hindsight: A SAS Macro for Retrospective Statistical Power Analysis Kristine Y. Hogarty,
Jeffrey D. Kromrey		 source 10
MWSUG 1998 A Tour of UnifyPow: A SAS Module/Macro for Sample-Size Analysis Ralph G. O'Brien 11
SESUG 1998 Computing a Test Statistic for Scale Parameters Based on a Jackknife Procedure Jean G. Orelien 6
SUGI 1998 A Tour of UnifyPow: A SAS Module/Macro for Sample-Size Analysis Ralph G. O'Brien source 10
SUGI 1997 UnifyPow: A SAS Macro for Sample-Size Analysis Ralph G. O'Brien source 6
WUSS 1996 Repeated Measures Analysis with the SAS System Kathleen Kierman source 10
SUGI 1995 A SAS Macro for the Assessment of Variability in Bioequivalence Trials Emmanuel Mohandoss,
Shein-Chung Chow		 source 5
SUGI 1995 Adjusted F-Tests for Repeated Measures with the MIXED Procedure S. Paul Wright source 6
SEUGI 1994 Analysis of Dose-response Curves in Molecular Pharmacology by the SAS System Paola Baiardi source 10
SUGI 1994 Introduction to Repeated Measures William G. LeBlanc source 9
SUGI 1994 Mixed Model Analysis of Data: Transition from GLM to MIXED Ramon C. Littell source 8
SEUGI 1993 A New Look at the Facilities in PROC MIXED James L. Roger source 12
SESUG 1993 Repeated Measures Using PROC MIXED Instead of PROC GLM James H. Roger,
Michael Kenward		 10
SUGI 1992 HOMOVAR: A Macro for Testing Homogeneity of Variances Kristin Latour source 5
SUGI 1991 About JMP 2.0 John P. Sall,
Katherine Ng,
Michael Hecht,
Ann Lehman		 source 6
SUGI 1989 Issues Related to Analyzing Repeated Measurement Data Ramon C. Littell,
Jane Pendergast		 source
SUGI 1988 Power Analysis in an Enhanced GLM Procedure: What It Might Look Like Ralph G. O'Brien,
S. Paul Wright		 source 6
SUGI 1988 Repeated Measures Analysis with the SAS System Ramon C. Littell,
Jane Pendergast		 source 7
SUGI 1988 The Analysis of Complete Blocks Using Methods Based on Ranks Ronald L. Iman source 9
SEUGI 1986 SAS/STAT Software on the IBM PC under PC DOS Gerhard Held source 12
SUGI 1986 Comparing Parameter Estimates Between Linear Models John E. Teberg source 7
SUGI 1986 Mixed Model Analyses with the SAS System Ramon C. Littell source 8
SUGI 1984 Power Analysis for Linear Models: The Time Has Come Virginia I. Lohr,
Ralph G. O'Brien		 source 7
SUGI 1981 Type I Error Rates for the Unequal Variance T Test J. Philip Miller,
Robert P. Parks,
Reimut Wette		 source

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