The GENMOD Procedure
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Overview
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Getting Started
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Syntax
PROC GENMOD Statement ASSESS Statement BAYES Statement BY Statement CLASS Statement CONTRAST Statement DEVIANCE Statement EFFECTPLOT Statement ESTIMATE Statement EXACT Statement EXACTOPTIONS Statement FREQ Statement FWDLINK Statement INVLINK Statement LSMEANS Statement LSMESTIMATE Statement MODEL Statement OUTPUT Statement Programming Statements REPEATED Statement SLICE Statement STORE Statement STRATA Statement VARIANCE Statement WEIGHT Statement ZEROMODEL Statement
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Details
Generalized Linear Models Theory Specification of Effects Parameterization Used in PROC GENMOD Type 1 Analysis Type 3 Analysis Confidence Intervals for Parameters F Statistics Lagrange Multiplier Statistics Predicted Values of the Mean Residuals Multinomial Models Zero-Inflated Models Generalized Estimating Equations Assessment of Models Based on Aggregates of Residuals Case Deletion Diagnostic Statistics Bayesian Analysis Exact Logistic and Exact Poisson Regression Missing Values Displayed Output for Classical Analysis Displayed Output for Bayesian Analysis Displayed Output for Exact Analysis ODS Table Names ODS Graphics
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Examples
Logistic Regression Normal Regression, Log Link Gamma Distribution Applied to Life Data Ordinal Model for Multinomial Data GEE for Binary Data with Logit Link Function Log Odds Ratios and the ALR Algorithm Log-Linear Model for Count Data Model Assessment of Multiple Regression Using Aggregates of Residuals Assessment of a Marginal Model for Dependent Data Bayesian Analysis of a Poisson Regression Model Exact Poisson Regression
- References
| LSMEANS Statement |
- LSMEANS <model-effects> </ options> ;
The LSMEANS statement computes and compares least squares means (LS-means) of fixed effects. LS-means are predicted population margins—that is, they estimate the marginal means over a balanced population. In a sense, LS-means are to unbalanced designs as class and subclass arithmetic means are to balanced designs.
Table 39.3 summarizes important options in the LSMEANS statement. If you specify the BAYES statement, the ADJUST=, STEPDOWN, and LINES options are ignored. The PLOTS= option is not available for a maximum likelihood analysis; it is available only for a Bayesian analysis.
If you specify a zero-inflated model (that is, a model for either the zero-inflated Poisson or the zero-inflated negative binomial distribution), then the least squares means are computed only for effects in the model for the distribution mean, and not for effects in the zero-inflation probability part of the model.
Option |
Description |
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Construction and Computation of LS-Means |
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Modifies the covariate value in computing LS-means |
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Computes separate margins |
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Requests differences of LS-means |
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Specifies the weighting scheme for LS-means computation as determined by the input data set |
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Tunes estimability checking |
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Degrees of Freedom and p-values |
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Determines the method for multiple comparison adjustment of LS-means differences |
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Determines the confidence level ( |
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Adjusts multiple comparison p-values further in a step-down fashion |
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Statistical Output |
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Constructs confidence limits for means and mean differences |
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Displays the correlation matrix of LS-means |
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Displays the covariance matrix of LS-means |
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Prints the |
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Produces a "Lines" display for pairwise LS-means differences |
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Prints the LS-means |
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Requests ODS statistical graphics of means and mean comparisons |
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Specifies the seed for computations that depend on random numbers |
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Generalized Linear Modeling |
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Exponentiates and displays estimates of LS-means or LS-means differences |
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Computes and displays estimates and standard errors of LS-means (but not differences) on the inverse linked scale |
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Reports (simple) differences of least squares means in terms of odds ratios if permitted by the link function |
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matrix For details about the syntax of the LSMEANS statement, see the section LSMEANS Statement of Chapter 19, Shared Concepts and Topics.