SAS Homework Help
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 Least squares regression with model selection techniques
 Diagnostic measures
 Robust regression
 Loess regression
 Nonlinear regression and quadratic response surface models
 Partial least squares regression
 Quantile regression
 Multivariate adaptive regression splines
Analysis of Variance
 Balanced and unbalanced designs
 Multivariate analysis of variance and repeated measurements
 Linear models
Categorical Data Analysis
 Contingency tables and measures of association
 Logistic regression and log linear models
 Bioassay analysis
 Generalized estimating equations
 Generalized linear models
 Exact methods
 Zeroinflated Poisson regression
 Zeroinflated negative binomial regression
Bayesian Analysis
 Bayesian modeling and inference for generalized linear models, accelerated failure time models, Cox regression models (piecewise constant baseline hazard) and finite mixture models
 General Bayesian statistical models with userspecified priors and likelihood functions
Mixed Models
 Linear mixed models
 Nonlinear mixed models
 Generalized linear mixed models
Multivariate Analysis
 Factor analysis
 Principal components
 Canonical correlation and discriminant analysis
 Path analysis
 Structural equation modeling
Psychometric Analysis
 Multidimensional scaling
 Conjoint analysis with variable transformations
 Correspondence analysis


Cluster Analysis
 Hierarchical clustering of multivariate data or distance data
 Disjoint clustering of large data sets
 Nonparametric clustering with hypothesis tests for the number of clusters
Survival Analysis
 Nonparametric estimation of survivor function
 Accelerated failure time models
 Proportional hazards models
 Quantile regression models
Nonparametric Analysis
 Nonparametric analysis of variance. Exact probabilities computed for many nonparametric statistics
 KruskalWallis, WilcoxonMannWhitney and Friedman tests
 Rank tests for balanced or unbalanced oneway or twoway designs
Survey Data Analysis
 Sample selection
 Descriptive statistics and ttests
 Linear and logistic regression
 Frequency table analysis
 Cox proportional hazards model
Multiple Imputation
 Regression and propensity score methods for monotone missing patterns
 MCMC method for arbitrary missing patterns
 Combine results for statistically valid inferences
Study Planning
 Power and Sample Size application provides interface for computation of sample sizes and characterization of power for ttests, confidence intervals, linear models, tests of proportions and rank tests for survival analysis
Multithreaded Procedures
Statistical Graphics
 ODS Statistical Graphics
 Scatter plots, diagnostic plots, histograms, boxandwhisker plots

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