These examples investigate a variety of analytical techniques that use SAS Software. The SAS statements and data sets that are used in the examples are available for download. The examples are categorized as follows:
NEW: Computing Marginal Effects for Discrete Dependent Variable Models
Testing for Returns to Scale in a Cobb-Douglas Production Function
Efficient Method of Moments Estimation of a Stochastic Volatility Model
Heteroscedastic Two-Stage Least Squares Regression with PROC MODEL
Bootstrapping Correct Critical Values in Tests for Structural Change
Bayesian Zero-Inflated Poisson Regression
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(616KB) |
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Bayesian Linear Regression with Standardized Covariates
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(307KB) |
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Bayesian Hierarchical Poisson Regression Model for Overdispersed Count Data
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(348KB) |
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Bayesian Binomial Model with Power Prior Using the MCMC Procedure
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(348KB) |
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Bayesian Multivariate Prior for Multiple Linear Regression
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(348KB) |
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Bayesian Multinomial Model for Ordinal Data
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(348KB) |
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