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Chapter 31: The GENMOD Procedure
Output 31.1.1: Model Information
Output 31.1.2: Class Variable Levels
Output 31.1.3: Goodness of Fit Criteria
Output 31.1.4: Parameter Estimates
Output 31.2.1: Log Linked Normal Regression
Output 31.2.2: Data Set of Predicted Values and Residuals
Output 31.3.1: Gamma Model of Life Data
Output 31.3.2: Refitting of the Gamma ModelOmitting the mfg Effect
Output 31.4.1: Ordinal Model Information
Output 31.4.2: Parameter Estimates
Output 31.4.3: Type 1 Tests and Odds Ratios
Output 31.5.1: Respiratory Disorder Data
Output 31.5.2: Model Fitting Information
Output 31.5.3: Results of Model Fitting
Output 31.6.1: Results of Model Fitting
Output 31.6.2: Full z-Matrix Data Set
Output 31.7.1: Partial Listing of the Seizure Data
Output 31.7.2: Independence Model
Output 31.7.3: GEE Model Information
Output 31.7.4: GEE Parameter Estimates
Output 31.7.5: Working Correlation Matrix
Output 31.7.6: Covariance Matrices
Output 31.8.1: Surgical Unit Example Data
Output 31.8.2: Regression Model for Linear X1
Output 31.8.3: Cumulative Residual Plot for Linear X1 Fit (Experimental)
Output 31.8.4: Cumulative Residual Panel Plot for Linear X1 Fit (Experimental)
Output 31.8.5: Summary of Model Assessment
Output 31.8.6: Typical Cumulative Residual Patterns
Output 31.8.8: Cumulative Residual Plot With Log(X1)(Experimental)
Output 31.8.7: Multiple Regression Model With Log(X1)
Output 31.9.1: Cumulative Residual Plot for Quadratic Time Fit (Experimental)
Output 31.9.2: Cumulative Residual Plot for Cubic Time Fit (Experimental)
Chapter 32: The GLM Procedure
Output 32.1.1: Classes and Levels for Randomized Complete Blocks
Output 32.1.2: Analysis of Variance for Randomized Complete Blocks
Output 32.1.3: Standard Analysis Again
Output 32.1.4: Contrasts and Solutions
Output 32.1.5: Waller-Duncan tests
Output 32.1.6: Ryan-Einot-Gabriel-Welsch Multiple Range Test
Output 32.2.1: Observations for Standard Regression Analysis
Output 32.2.2: Standard Analysis of Variance for Regression
Output 32.2.3: Results of Requesting the P and CLM Options
Output 32.2.4: Additional Results of Requesting the P and CLM Options
Output 32.2.5: Plot of Mileage Data
Output 32.3.1: Classes and Levels for Unbalanced Two-Way Design
Output 32.3.2: Analysis of Variance for Unbalanced Two-Way Design
Output 32.3.3: LS-Means for Unbalanced ANOVA
Output 32.4.1: Overall Analysis of Variance
Output 32.4.2: Tests and Parameter Estimates
Output 32.4.3: LS-means
Output 32.4.4: LS-means Output Data Set
Output 32.4.5: Analysis of Covariance Plot (Experimental)
Output 32.5.1: Overall Analysis
Output 32.5.2: Individual Effects and Contrasts
Output 32.5.3: Simple Effects of Time
Output 32.5.4: Contents of the OUTSTAT= Data Set
Output 32.6.1: Summary Information on Groups
Output 32.6.2: Univariate Analysis of Variance for Aluminum Oxide
Output 32.6.3: Univariate Analysis of Variance for Iron Oxide
Output 32.6.4: Univariate Analysis of Variance for Calcium Oxide
Output 32.6.5: Univariate Analysis of Variance for Magnesium Oxide
Output 32.6.6: Univariate Analysis of Variance for Sodium Oxide
Output 32.6.7: Error SSCP Matrix and Partial Correlations
Output 32.6.8: Hypothesis SSCP Matrix and Multivariate Tests for Overall Site Effect
Output 32.6.9: Hypothesis SSCP Matrix and Multivariate Tests for Differences Between Llanederyn and the Rest
Output 32.7.1: Summary Information on Groups
Output 32.7.2: Repeated Measures Levels
Output 32.7.3: Multivariate Tests of Within-Subject Effects
Output 32.7.4: Tests of Between-Subject Effects
Output 32.7.5: Sphericity Test
Output 32.7.6: Univariate Tests of Within-Subject Effects
Output 32.7.7: Tests of Between-Subject Effects for Transformed Variables
Output 32.8.1: Summary Information on Groups
Output 32.8.2: Fixed-Effect Model Analysis of Variance
Output 32.8.3: Expected Values of Type III Mean Squares
Output 32.8.4: Mixed Model Analysis of Variance
Output 32.8.5: PROC MIXED Mixed Model Analysis of Variance (Partial Output)
Output 32.9.1: A Doubly-multivariate Repeated Measures Design
Output 32.9.2: Repeated Factor Levels
Output 32.9.3: Within-subject Tests
Output 32.9.4: M Matrix to Test for Time Effect (Repeated Measure)
Output 32.9.5: Tests for Time Effect (Repeated Measure)
Output 32.9.6: Summary Output for the Test for Time Effect
Output 32.10.1: Usual ANOVA Test for Age Group Differences in Mean Olfactory Index
Output 32.10.2: Levenes Test for Age Group Differences in Olfactory Variability
Output 32.10.3: Welchs Test for Age Group Differences in Mean Olfactory Index
Output 32.11.1: Analysis of Variance for Nitride Etch Process Half Fraction
Output 32.11.2: Parameter Estimates and Aliases for Nitride Etch Process Half Fraction
Output 32.11.3: Analysis of Variance for Nitride Etch Process Full Replicate
Chapter 33: The GLMMOD Procedure
Output 33.1.1: A Two-Way Design
Output 33.1.2: The OUTPARM= Data Set
Output 33.1.3: The OUTDESIGN= Data Set
Output 33.2.1: PROC REG Full Model Fit
Output 33.2.2: PROC REG Screening Results
Chapter 34: The GLMPOWER Procedure
Output 34.1.1: Sample Sizes for One-Way ANOVA Contrasts
Output 34.1.2: Plot of Sample Size versus Power for One-Way ANOVA Contrasts
Output 34.1.3: Plot of Power versus Sample Size for One-Way ANOVA Contrasts
Output 34.2.1: Sample Sizes for Two-Way ANOVA Contrasts
Output 34.2.2: Plot of Sample Size versus Power for Two-Way ANOVA Contrasts
Output 34.2.3: Plot of Power versus Sample Size for Two-Way ANOVA Contrasts
Chapter 35: The INBREED Procedure
Output 35.1.1: Monoecious Population Analysis
Output 35.2.1: Pedigree Analysis
Output 35.3.1: Pedigree Analysis with BY Groups
Chapter 36: The KDE Procedure
Output 36.1.1: Histogram with Overlaid Kernel Density Estimate (Experimental)
Output 36.2.1: Histogram with Oversmoothed Kernel Density Estimate (Experimental)
Output 36.2.2: Histogram with Undersmoothed Kernel Density Estimate (Experimental)
Output 36.3.1: Contour Plot of Estimated Density with Additional Smoothing (Experimental)
Output 36.3.2: Contour Plot of Estimated Density with Different Smoothing for x and y (Experimental)
Output 36.5.1: Surface Plot of the Bivariate Kernel Density Estimate
Output 36.5.2: Contour Plot of the Bivariate Kernel Density Estimate
Output 36.5.3: Contour Plot of the Bivariate Kernel Density Estimate with Levels Corresponding to Percentiles
Output 36.6.1: Histogram (Experimental)
Output 36.6.2: Kernel Density Estimate (Experimental)
Output 36.6.3: Histogram with Overlaid Kernel Density Estimate (Experimental)
Output 36.7.1: Scatter Plot (Experimental)
Output 36.7.2: Bivariate Histogram (Experimental)
Output 36.7.3: Contour Plot (Experimental)
Output 36.7.4: Contour Plot with Overlaid Scatter Plot (Experimental)
Output 36.7.5: Surface Plot (Experimental)
Output 36.7.6: Bivariate Histogram with Overlaid Surface Plot (Experimental)
Chapter 37: The KRIGE2D Procedure
Output 37.1.1: Comparison of Gaussian and Spherical Models
Chapter 38: The LATTICE Procedure
Output 38.1.1: Displayed Output from PROC PRINT
Output 38.1.2: Displayed Output from PROC LATTICE
Chapter 39: The LIFEREG Procedure
Output 39.1.1: Motorette Failure Data
Output 39.1.2: Motorette FailureModel A
Output 39.1.3: Motorette FailureModel B
Output 39.1.4: Motorette FailureFitted Models
Output 39.1.5: Motorette FailureQuantile Estimates and Confidence Limits
Output 39.2.1: Parameter Estimates from PROC LIFEREG
Output 39.2.2: Predicted Means from PROC LIFEREG
Output 39.3.1: Contents of the Data Set
Output 39.3.2: Initial Least Squares
Output 39.3.3: Estimates from the Log Logistic Distribution
Output 39.3.4: Final Estimates from the Weibull Distribution
Output 39.4.1: Parameter Estimates for the Interaction Model
Output 39.4.2: Probability Plot for Recovery Time with sex =1,age =50
Output 39.4.3: Probability Plot for Recovery Time with sex =2, age = 60.6
Output 39.5.1: Probability Plot for the Fan Data
Output 39.5.2: CDF Estimates
Output 39.6.1: Iteration History for the Turnbull Estimate
Output 39.6.2: Summary for the Turnbull Algorithm
Output 39.6.3: Final CDF Estimates for Turnbull Algorithm
Output 39.6.4: Lognormal Probability Plot for the Microprocessor Data
Chapter 40: The LIFETEST Procedure
Output 40.1.1: Estimation Results for Cell =adeno
Output 40.1.2: Estimation Results for Cell=large
Output 40.1.3: Estimation Results for Cell=small
Output 40.1.4: Estimation Results for Cell=squamous
Output 40.1.5: Summary of Censored and Uncensored Values
Output 40.1.6: Graph of the Estimated Survivor Functions
Output 40.1.7: Graph of Negative Log of the Estimated Survivor Functions
Output 40.1.8: Graph of Log of the Negative Log of the Estimated Survivor Functions
Output 40.1.9: Homogeneity Tests Across Strata
Output 40.1.10: Log-Rank Test of the Prognostic Factors
Output 40.1.11: Log-Rank Statistics and Covariance Matrix
Output 40.1.12: Best Subset Regression from the REG Procedure
Output 40.2.1: Variables in the Out1 Data Set
Output 40.2.2: Panel Plot for ALL Patients (Experimental)
Output 40.2.3: Product-Limit Estimates of Survival of Bone Marrow Transplant Patients (Experimental)
Output 40.2.4: Hall-Wellner Bands for the Survival of Bone Marrow Transplant Patients (Experimental)
Output 40.3.1: Life-Table Survivor Function Estimate
Output 40.3.2: Summary of Censored and Event Observations
Output 40.3.3: Life-Table Survivor Function Estimate
Output 40.3.4: Negative Log of Survivor Function Estimate
Output 40.3.5: Log of Negative Log of Survivor Function Estimate
Output 40.3.6: Hazard Function Estimate
Output 40.3.7: Density Function Estimate
Chapter 41: The LOESS Procedure
Output 41.1.1: Scatter Plot of Gas Data
Output 41.1.2: Fit Summary Table
Output 41.1.3: Output Statistics Table
Output 41.1.4: Loess Fits with 99% Confidence Bands for Gas Data
Output 41.1.5: Scatter Plots of Loess Fit Residuals
Output 41.1.6: Test ANOVA for LOESS MODELS of Gas Data
Output 41.2.1: Locations of Sulfate Measurements
Output 41.2.2: Scatter Plot of SO4 Data
Output 41.2.3: Scatter Plots of Loess Fit Residuals
Output 41.2.4: LOESS Fit of SO4 Data
Output 41.2.5: Contour Plot of LOESS Fit of SO4 Data
Output 41.3.1: Surface Plot of Experiment Data
Output 41.3.2: Scale Details Table
Output 41.3.3: Fitted Surface Plot for Experiment Data
Output 41.4.1: Scatter Plot of ENSO Data
Output 41.4.2: Output from PROC LOESS
Output 41.4.3: Oversmoothed Loess Fit for the ENSO Data
Output 41.4.4: AICC versus Smoothing Parameter Showing Local Minima
Output 41.4.5: Loess Fit for the ENSO Data
Output 41.5.1: Smoothing Parameter Selection (Experimental)
Output 41.5.2: LOESS Fit of ENSO Data (Experimental)
Output 41.5.3: Residuals by Regressors (Experimental)
Output 41.5.4: Fit Diagnostics Panel (Experimental)
Output 41.5.5: Residual Histogram (Experimental)
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Table of content
SAS/STAT 9.1, Users Guide, Volume 3 (volume 3 ONLY)
ISBN: B0042UQTBS
EAN: N/A
Year: 2004
Pages: 105
BUY ON AMAZON
The Complete Cisco VPN Configuration Guide
Summary
IPsec Remote Access
Summary
Troubleshooting PIX and ASA Connections
Summary
Introducing Microsoft ASP.NET AJAX (Pro - Developer)
The AJAX Revolution
The Pulsing Heart of ASP.NET AJAX
Partial Page Rendering
Built-in Application Services
Remote Method Calls with ASP.NET AJAX
Persuasive Technology: Using Computers to Change What We Think and Do (Interactive Technologies)
Overview of Captology
Computers as Persuasive Media Simulation
Computers as Persuasive Social Actors
Credibility and Computers
The Ethics of Persuasive Technology
.NET-A Complete Development Cycle
References for Further Reading
The Photo Editor Application
Conclusion: Dont Reinvent the Wheel
Requirements for Performance Optimization
Analysis of the Editor Optimization Requirement
Cultural Imperative: Global Trends in the 21st Century
From 2,000,000 B.C. to A.D.2000: The Roots and Routes of Culture
Culture and Climate
Cross-Century Worldviews
Cognitive Processes
Epilogue After September 11
Digital Character Animation 3 (No. 3)
Creating Characters
Chapter Six. Walking and Locomotion
Conclusion
Four-Legged Mammals
Acting Vs. Animating
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