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SAS/STAT

SAS/STAT User's Guide - Procedures

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SAS/STAT 13.1 User's Guide - Procedures

For the complete SAS/STAT 13.1 User's Guide, go to the SAS/STAT product documentation page.

  • The ACECLUS Procedure
    Obtains approximate estimates of the pooled within-cluster covariance matrix when the clusters are assumed to be multivariate normal with equal covariance matrices.
    PDF (2.39MB)  |   HTML
  • The ADAPTIVEREG Procedure
    Fits multivariate adaptive regression splines.
    PDF (4.42MB)  |   HTML
  • The ANOVA Procedure
    Performs analysis of variance for balanced data.
    PDF (2.26MB)  |   HTML
  • The BCHOICE Procedure (Experimental)
    Performs Bayesian analysis for discrete choice models.
    PDF (2.71MB)  |   HTML
  • The BOXPLOT Procedure
    Creates side-by-side box-and-whiskers plots of measurements organized in groups.
    PDF (2.72MB)  |   HTML
  • The CALIS Procedure
    Fits structural equation models.
    PDF (7.62MB)  |   HTML
  • The CANCORR Procedure
    Performs canonical correlation, partial canonical correlation, and canonical redundancy analysis.
    PDF (2.11MB)  |   HTML
  • The CANDISC Procedure
    Performs a canonical discriminant analysis, computes squared Mahalanobis distances between class means, and performs both univariate and multivariate one-way analyses of variance.
    PDF (2.23MB)  |   HTML
  • The CATMOD Procedure
    Performs categorical data modeling of data that can be represented by a contingency table.
    PDF (2.45MB)  |   HTML
  • The CLUSTER Procedure
    Hierarchically clusters the observations in a SAS data.
    PDF (4.44MB)  |   HTML
  • The CORRESP Procedure
    Performs simple correspondence analysis and multiple correspondence analysis (MCA).
    PDF (2.57MB)  |   HTML
  • The DISCRIM Procedure
    Develops a discriminant criterion to classify each observation into groups.
    PDF (3.91MB)  |   HTML
  • The DISTANCE Procedure
    Computes various measures of distance, dissimilarity, or similarity between the observations (rows) of a SAS data set. Proximity measures are stored as a lower triangular matrix or a square matrix in an output data set that can then be used as input to the CLUSTER, MDS, and MODECLUS procedures.
    PDF (2.59MB)  |   HTML
  • The FACTOR Procedure
    Performs a variety of common factor and component analyses and rotations.
    PDF (2.78MB)  |   HTML
  • The FASTCLUS Procedure
    Performs a disjoint cluster analysis on the basis of distances computed from one or more quantitative variables.
    PDF (2.66MB)  |   HTML
  • The FMM Procedure
    Fits finite mixture models.
    PDF (3.74MB)  |   HTML
  • The FREQ Procedure
    Produces one-way to n-way frequency and contingency (crosstabulation) tables and performs table analysis.
    PDF (3.33MB)  |   HTML
  • The GAM Procedure
    Fits generalized additive models.
    PDF (3.01MB)  |   HTML
  • The GENMOD Procedure
    Fits generalized linear models.
    PDF (4.42MB)  |   HTML
  • The GLIMMIX Procedure
    Fits generalized linear mixed models.
    PDF (6.11MB)  |   HTML
  • The GLM Procedure
    Fits general linear models.
    PDF (3.75MB)  |   HTML
  • The GLMMOD Procedure
    Constructs the design matrix for a general linear model; it essentially constitutes the model-building front end for the GLM procedure.
    PDF (2.03MB)  |   HTML
  • The GLMPOWER Procedure
    Performs prospective power and sample size analysis for linear models.
    PDF (2.29MB)  |   HTML
  • The GLMSELECT Procedure
    Performs effect selection in the framework of general linear models.
    PDF (5.91MB)  |   HTML
  • The HPMIXED Procedure
    Fits linear mixed models with simple covariance component structures by sparse-matrix techniques.
    PDF (2.58MB)  |   HTML
  • The ICLIFETEST Procedure
    Performs nonparametric survival analysis for interval-censored data.
    PDF (2.75MB)  |   HTML
  • The INBREED Procedure
    Calculates the covariance or inbreeding coefficients for a pedigree.
    PDF (2.12MB)  |   HTML
  • The IRT Procedure (Experimental)
    Fits item response models.
    PDF (2.56MB)  |   HTML
  • The KDE Procedure
    Performs univariate and bivariate kernel density estimation.
    PDF (3.78MB)  |   HTML
  • The KRIGE2D Procedure
    Performs ordinary kriging in two dimensions.
    PDF (7.06MB)  |   HTML
  • The LATTICE Procedure
    Performs analysis of variance and analysis of simple covariance for data from experiments with lattice designs.
    PDF (2.0MB)  |   HTML
  • The LIFEREG Procedure
    Fits parametric models to failure time data that can be uncensored, right censored, left censored, or interval censored.
    PDF (3.68MB)  |   HTML
  • The LIFETEST Procedure
    Computes nonparametric estimates of the survivor function either by the product-limit method (also called the Kaplan-Meier method) or by the lifetable method (also called the actuarial method).
    PDF (3.53MB)  |   HTML
  • The LOESS Procedure
    Implements a nonparametric method for estimating regression surfaces.
    PDF (4.31MB)  |   HTML
  • The LOGISTIC Procedure
    Fits regression models with binary, ordinal, or nominal dependent variables.
    PDF (5.02MB)  |   HTML
  • The MCMC Procedure
    Performs general-purpose Markov chain Monte Carlo (MCMC) simulation designed to fit Bayesian models.
    PDF (6.07MB)  |   HTML
  • The MDS Procedure
    Fits two- and three-way, metric and nonmetric multidimensional scaling models.
    PDF (3.16MB)  |   HTML
  • The MI Procedure
    Performs multiple imputation of missing data.
    PDF (3.21MB)  |   HTML
  • The MIANALYZE Procedure
    Combines the results of the analyses of imputations and generates valid statistical inferences.
    PDF (2.23MB)  |   HTML
  • The MIXED Procedure
    Fits general linear models with fixed and random effects.
    PDF (4.17MB)  |   HTML
  • The MODECLUS Procedure
    Clusters observations in a SAS data set by using any of several algorithms based on nonparametric density estimates.
    PDF (5.95MB)  |   HTML
  • The MULTTEST Procedure
    Addresses the multiple testing problem by adjusting the p-values from a family of hypothesis tests.
    PDF (2.97MB)  |   HTML
  • The NESTED Procedure
    Performs random-effects analysis of variance for data from an experiment with a nested (hierarchical) structure and classification effects.
    PDF (2.05MB)  |   HTML
  • The NLIN Procedure
    Fits nonlinear regression models.
    PDF (3.66MB)  |   HTML
  • The NLMIXED Procedure
    Fits mixed models in which the fixed or random effects enter nonlinearly.
    PDF (2.81MB)  |   HTML
  • The NPAR1WAY Procedure
    Performs nonparametric tests for location and scale differences across a one-way classification.
    PDF (2.49MB)  |   HTML
  • The ORTHOREG Procedure
    Fits general linear models by the method of least squares and provides more accurate estimates than other procedures when your data are ill-conditioned.
    PDF (2.20MB)  |   HTML
  • The PHREG Procedure
    Performs regression analysis of survival data based on the Cox proportional hazards model.
    PDF (4.39MB)  |   HTML
  • The PLAN Procedure
    Constructs designs and randomizes plans for factorial experiments.
    PDF (2.09MB)  |   HTML
  • The PLM Procedure
    Performs postfitting statistical analyses.
    PDF (2.53MB)  |   HTML
  • The PLS Procedure
    Performs principal component regression.
    PDF (4.62MB)  |   HTML
  • The POWER Procedure
    Performs prospective power and sample size analyses for a variety of statistical analyses.
    PDF (7.03MB)  |   HTML
  • The Power and Sample Size Application
    PDF (4.26MB)  |   HTML
  • The PRINCOMP Procedure
    Performs principal component analysis.
    PDF (3.79MB)  |   HTML
  • The PRINQUAL Procedure
    Performs principal component analysis (PCA) of qualitative, quantitative, or mixed data.
    PDF (3.58MB)  |   HTML
  • The PROBIT Procedure
    Calculates maximum likelihood estimates of regression parameters and the natural (or threshold) response rate for quantal response data from biological assays or other discrete event data.
    PDF (3.22MB)  |   HTML
  • The QUANTLIFE Procedure
    Performs quantile regression analysis for survival data.
    PDF (2.78MB)  |   HTML
  • The QUANTREG Procedure
    Fits quantile regression models.
    PDF (4.77MB)  |   HTML
  • The QUANTSELECT Procedure
    Performs effect selection in the framework of quantile regression.
    PDF (3.17MB)  |   HTML
  • The REG Procedure
    General-purpose procedure for ordinary least squares regression.
    PDF (6.92MB)  |   HTML
  • The ROBUSTREG Procedure
    Provides resistant (stable) results for linear regression models in the presence of outliers.
    PDF (4.15MB)  |   HTML
  • The RSREG Procedure
    Fits quadratic response surface regression models.
    PDF (2.67MB)  |   HTML
  • The SCORE Procedure
    Multiplies values from two SAS data sets, one containing coefficients and the other containing raw data to be scored using the coefficients from the first data set.
    PDF (2.08MB)  |   HTML
  • The SEQDESIGN Procedure
    Designs interim analyses for group sequential clinical trials.
    PDF (6.74MB)  |   HTML
  • The SEQTEST Procedure
    Performs interim analyses for group sequential clinical trials.
    PDF (5.54MB)  |   HTML
  • The SIM2D Procedure
    Produces a spatial simulation for a Gaussian random field with a specified mean and covariance structure in two dimensions by using an LU decomposition technique.
    PDF (4.13MB)  |   HTML
  • The SIMNORMAL Procedure
    Performs conditional and unconditional simulation for a set of correlated normal or Gaussian random variables.
    PDF (2.17MB)  |   HTML
  • The STDIZE Procedure
    Standardizes one or more numeric variables in a SAS data set by subtracting a location measure and dividing by a scale measure.
    PDF (2.19MB)  |   HTML
  • The STDRATE Procedure
    Computes directly standardized rates and risks for study populations.
    PDF (3.02MB)  |   HTML
  • The STEPDISC Procedure
    Given a classification variable and several quantitative variables, the procedure performs a stepwise discriminant analysis to select a subset of the quantitative variables for use in discriminating among the classes.
    PDF (2.07MB)  |   HTML
  • The SURVEYFREQ Procedure
    Produces one-way to n-way frequency and crosstabulation tables from complex multistage survey designs with stratification, clustering, and unequal weighting.
    PDF (2.67MB)  |   HTML
  • The SURVEYLOGISTIC Procedure
    Fits models with binary, ordinal, or nominal dependent variables and incorporates complex survey designs.
    PDF (2.50MB)  |   HTML
  • The SURVEYMEANS Procedure
    Estimate statistics such as means, totals, proportions, quantiles, and ratios from complex multistage survey designs with stratification, clustering, and unequal weighting.
    PDF (2.55MB)  |   HTML
  • The SURVEYPHREG Procedure
    Performs regression analysis of survival data based on the Cox proportional hazards model for complex survey sample designs.
    PDF (2.42MB)  |   HTML
  • The SURVEYREG Procedure
    Performs linear regression analysis for complex survey sample designs.
    PDF (3.0MB)  |   HTML
  • The SURVEYSELECT Procedure
    Selects simple random samples or selects samples according to a complex multistage sample design that includes stratification, clustering, and unequal probabilities of selection.
    PDF (2.35MB)  |   HTML
  • The TPSPLINE Procedure
    Provides penalized least squares estimates.
    PDF (4.19MB)  |   HTML
  • The TRANSREG Procedure
    Fits linear models with optimal nonlinear transformations of variables.
    PDF (10.0MB)  |   HTML
  • The TREE Procedure
    Produces a tree diagram, also known as a dendrogram or phenogram, from a data set created by the CLUSTER or VARCLUS procedure that contains the results of hierarchical clustering as a tree structure.
    PDF (2.54MB)  |   HTML
  • The TTEST Procedure
    Performs t tests and computes confidence limits for one sample, paired observations, two independent samples, and the AB/BA crossover design.
    PDF (4.04MB)  |   HTML
  • The VARCLUS Procedure
    Divides a set of numeric variables into disjoint or hierarchical clusters.
    PDF (2.15MB)  |   HTML
  • The VARCOMP Procedure
    Fits general linear models with random effects (with the option of specifying certain effects as fixed).
    PDF (2.16MB)  |   HTML
  • The VARIOGRAM Procedure
    Computes empirical measures of spatial continuity for two-dimensional spatial data.
    PDF (5.43MB)  |   HTML


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SAS/STAT 12.3 User's Guide - Procedures

Note: SAS/STAT 12.3 is essentially a maintenance release, with the exception that high-performance procedures for use in single-machine mode have been added. The SAS/STAT 12.3 documentation applies to both SAS/STAT 12.3 and 12.1.


For the complete SAS/STAT 12.3 User's Guide, go to the SAS/STAT product documentation page.

  • The ACECLUS Procedure
    Obtains approximate estimates of the pooled within-cluster covariance matrix when the clusters are assumed to be multivariate normal with equal covariance matrices.
    PDF (2.35MB)  |   HTML
  • The ADAPTIVEREG Procedure (Experimental)
    Fits multivariate adaptive regression splines.
    PDF (4.19MB)  |   HTML
  • The ANOVA Procedure
    Performs analysis of variance for balanced data.
    PDF (2.21MB)  |   HTML
  • The BOXPLOT Procedure
    Creates side-by-side box-and-whiskers plots of measurements organized in groups.
    PDF (2.66MB)  |   HTML
  • The CALIS Procedure
    Fits structural equation models.
    PDF (4.7MB)  |   HTML
  • The CANCORR Procedure
    Performs canonical correlation, partial canonical correlation, and canonical redundancy analysis.
    PDF (2.07MB)  |   HTML
  • The CANDISC Procedure
    Performs a canonical discriminant analysis, computes squared Mahalanobis distances between class means, and performs both univariate and multivariate one-way analyses of variance.
    PDF (2.22MB)  |   HTML
  • The CATMOD Procedure
    Performs categorical data modeling of data that can be represented by a contingency table.
    PDF (2.41MB)  |   HTML
  • The CLUSTER Procedure
    Hierarchically clusters the observations in a SAS data.
    PDF (4.41MB)  |   HTML
  • The CORRESP Procedure
    Performs simple correspondence analysis and multiple correspondence analysis (MCA).
    PDF (2.53MB)  |   HTML
  • The DISCRIM Procedure
    Develops a discriminant criterion to classify each observation into groups.
    PDF (3.86MB)  |   HTML
  • The DISTANCE Procedure
    Computes various measures of distance, dissimilarity, or similarity between the observations (rows) of a SAS data set. Proximity measures are stored as a lower triangular matrix or a square matrix in an output data set that can then be used as input to the CLUSTER, MDS, and MODECLUS procedures.
    PDF (2.54MB)  |   HTML
  • The FACTOR Procedure
    Performs a variety of common factor and component analyses and rotations.
    PDF (2.74MB)  |   HTML
  • The FASTCLUS Procedure
    Performs a disjoint cluster analysis on the basis of distances computed from one or more quantitative variables.
    PDF (2.62MB)  |   HTML
  • The FMM Procedure
    Fits finite mixture models.
    PDF (3.22MB)  |   HTML
  • The FREQ Procedure
    Produces one-way to n-way frequency and contingency (crosstabulation) tables and performs table analysis.
    PDF (3.24MB)  |   HTML
  • The GAM Procedure
    Fits generalized additive models.
    PDF (2.98MB)  |   HTML
  • The GENMOD Procedure
    Fits generalized linear models.
    PDF (4.35MB)  |   HTML
  • The GLIMMIX Procedure
    Fits generalized linear mixed models.
    PDF (6.04MB)  |   HTML
  • The GLM Procedure
    Fits general linear models.
    PDF (3.71MB)  |   HTML
  • The GLMMOD Procedure
    Constructs the design matrix for a general linear model; it essentially constitutes the model-building front end for the GLM procedure.
    PDF (1.98MB)  |   HTML
  • The GLMPOWER Procedure
    Performs prospective power and sample size analysis for linear models.
    PDF (2.92MB)  |   HTML
  • The GLMSELECT Procedure
    Performs effect selection in the framework of general linear models.
    PDF (4.76MB)  |   HTML
  • The HPMIXED Procedure
    Fits linear mixed models with simple covariance component structures by sparse-matrix techniques.
    PDF (2.43MB)  |   HTML
  • The INBREED Procedure
    Calculates the covariance or inbreeding coefficients for a pedigree.
    PDF (2.09MB)  |   HTML
  • The KDE Procedure
    Performs univariate and bivariate kernel density estimation.
    PDF (3.67MB)  |   HTML
  • The KRIGE2D Procedure
    Performs ordinary kriging in two dimensions.
    PDF (6.99MB)  |   HTML
  • The LATTICE Procedure
    Performs analysis of variance and analysis of simple covariance for data from experiments with lattice designs.
    PDF (1.98MB)  |   HTML
  • The LIFEREG Procedure
    Fits parametric models to failure time data that can be uncensored, right censored, left censored, or interval censored.
    PDF (3.6MB)  |   HTML
  • The LIFETEST Procedure
    Computes nonparametric estimates of the survivor function either by the product-limit method (also called the Kaplan-Meier method) or by the lifetable method (also called the actuarial method).
    PDF (3.49MB)  |   HTML
  • The LOESS Procedure
    Implements a nonparametric method for estimating regression surfaces.
    PDF (4.22MB)  |   HTML
  • The LOGISTIC Procedure
    Fits regression models with binary, ordinal, or nominal dependent variables.
    PDF (4.82MB)  |   HTML
  • The MCMC Procedure
    Performs general-purpose Markov chain Monte Carlo (MCMC) simulation designed to fit Bayesian models.
    PDF (6.02MB)  |   HTML
  • The MDS Procedure
    Fits two- and three-way, metric and nonmetric multidimensional scaling models.
    PDF (3.13MB)  |   HTML
  • The MI Procedure
    Performs multiple imputation of missing data.
    PDF (2.93MB)  |   HTML
  • The MIANALYZE Procedure
    Combines the results of the analyses of imputations and generates valid statistical inferences.
    PDF (2.17MB)  |   HTML
  • The MIXED Procedure
    Fits general linear models with fixed and random effects.
    PDF (3.93MB)  |   HTML
  • The MODECLUS Procedure
    Clusters observations in a SAS data set by using any of several algorithms based on nonparametric density estimates.
    PDF (5.74MB)  |   HTML
  • The MULTTEST Procedure
    Addresses the multiple testing problem by adjusting the p-values from a family of hypothesis tests.
    PDF (2.87MB)  |   HTML
  • The NESTED Procedure
    Performs random-effects analysis of variance for data from an experiment with a nested (hierarchical) structure and classification effects.
    PDF (2.01MB)  |   HTML
  • The NLIN Procedure
    Fits nonlinear regression models.
    PDF (3.26MB)  |   HTML
  • The NLMIXED Procedure
    Fits mixed models in which the fixed or random effects enter nonlinearly.
    PDF (2.54MB)  |   HTML
  • The NPAR1WAY Procedure
    Performs nonparametric tests for location and scale differences across a one-way classification.
    PDF (2.45MB)  |   HTML
  • The ORTHOREG Procedure
    Fits general linear models by the method of least squares and provides more accurate estimates than other procedures when your data are ill-conditioned.
    PDF (2.16MB)  |   HTML
  • The PHREG Procedure
    Performs regression analysis of survival data based on the Cox proportional hazards model.
    PDF (4.2MB)  |   HTML
  • The PLAN Procedure
    Constructs designs and randomizes plans for factorial experiments.
    PDF (2.05MB)  |   HTML
  • The PLM Procedure
    Performs postfitting statistical analyses.
    PDF (2.47MB)  |   HTML
  • The PLS Procedure
    Performs principal component regression.
    PDF (4.47MB)  |   HTML
  • The POWER Procedure
    Performs prospective power and sample size analyses for a variety of statistical analyses.
    PDF (6.89MB)  |   HTML
  • The Power and Sample Size Application
    PDF (4.23MB)  |   HTML
  • The PRINCOMP Procedure
    Performs principal component analysis.
    PDF (3.78MB)  |   HTML
  • The PRINQUAL Procedure
    Performs principal component analysis (PCA) of qualitative, quantitative, or mixed data.
    PDF (3.6MB)  |   HTML
  • The PROBIT Procedure
    Calculates maximum likelihood estimates of regression parameters and the natural (or threshold) response rate for quantal response data from biological assays or other discrete event data.
    PDF (3.13MB)  |   HTML
  • The QUANTLIFE Procedure (Experimental)
    Performs quantile regression analysis for survival data.
    PDF (2.7MB)  |   HTML
  • The QUANTREG Procedure
    Fits quantile regression models.
    PDF (4.27MB)  |   HTML
  • The QUANTSELECT Procedure (Experimental)
    Performs effect selection in the framework of quantile regression.
    PDF (2.49MB)  |   HTML
  • The REG Procedure
    General-purpose procedure for ordinary least squares regression.
    PDF (7.03MB)  |   HTML
  • The ROBUSTREG Procedure
    Provides resistant (stable) results for linear regression models in the presence of outliers.
    PDF (3.92MB)  |   HTML
  • The RSREG Procedure
    Fits quadratic response surface regression models.
    PDF (2.6MB)  |   HTML
  • The SCORE Procedure
    Multiplies values from two SAS data sets, one containing coefficients and the other containing raw data to be scored using the coefficients from the first data set.
    PDF (2.05MB)  |   HTML
  • The SEQDESIGN Procedure
    Designs interim analyses for group sequential clinical trials.
    PDF (6.75MB)  |   HTML
  • The SEQTEST Procedure
    Performs interim analyses for group sequential clinical trials.
    PDF (5.53MB)  |   HTML
  • The SIM2D Procedure
    Produces a spatial simulation for a Gaussian random field with a specified mean and covariance structure in two dimensions by using an LU decomposition technique.
    PDF (4.07MB)  |   HTML
  • The SIMNORMAL Procedure
    Performs conditional and unconditional simulation for a set of correlated normal or Gaussian random variables.
    PDF (2.13MB)  |   HTML
  • The STDIZE Procedure
    Standardizes one or more numeric variables in a SAS data set by subtracting a location measure and dividing by a scale measure.
    PDF (2.16MB)  |   HTML
  • The STDRATE Procedure
    Computes directly standardized rates and risks for study populations.
    PDF (2.92MB)  |   HTML
  • The STEPDISC Procedure
    Given a classification variable and several quantitative variables, the procedure performs a stepwise discriminant analysis to select a subset of the quantitative variables for use in discriminating among the classes.
    PDF (2.02MB)  |   HTML
  • The SURVEYFREQ Procedure
    Produces one-way to n-way frequency and crosstabulation tables from complex multistage survey designs with stratification, clustering, and unequal weighting.
    PDF (2.6MB)  |   HTML
  • The SURVEYLOGISTIC Procedure
    Fits models with binary, ordinal, or nominal dependent variables and incorporates complex survey designs.
    PDF (2.45MB)  |   HTML
  • The SURVEYMEANS Procedure
    Estimate statistics such as means, totals, proportions, quantiles, and ratios from complex multistage survey designs with stratification, clustering, and unequal weighting.
    PDF (2.31MB)  |   HTML
  • The SURVEYPHREG Procedure
    Performs regression analysis of survival data based on the Cox proportional hazards model for complex survey sample designs.
    PDF (2.38MB)  |   HTML
  • The SURVEYREG Procedure
    Performs linear regression analysis for complex survey sample designs.
    PDF (2.43MB)  |   HTML
  • The SURVEYSELECT Procedure
    Selects simple random samples or selects samples according to a complex multistage sample design that includes stratification, clustering, and unequal probabilities of selection.
    PDF (2.29MB)  |   HTML
  • The TPSPLINE Procedure
    Provides penalized least squares estimates.
    PDF (4.2MB)  |   HTML
  • The TRANSREG Procedure
    Fits linear models with optimal nonlinear transformations of variables.
    PDF (9.91MB)  |   HTML
  • The TREE Procedure
    Produces a tree diagram, also known as a dendrogram or phenogram, from a data set created by the CLUSTER or VARCLUS procedure that contains the results of hierarchical clustering as a tree structure.
    PDF (2.52MB)  |   HTML
  • The TTEST Procedure
    Performs t tests and computes confidence limits for one sample, paired observations, two independent samples, and the AB/BA crossover design.
    PDF (4.01MB)  |   HTML
  • The VARCLUS Procedure
    Divides a set of numeric variables into disjoint or hierarchical clusters.
    PDF (2.12MB)  |   HTML
  • The VARCOMP Procedure
    Fits general linear models with random effects (with the option of specifying certain effects as fixed).
    PDF (2.12MB)  |   HTML
  • The VARIOGRAM Procedure
    Computes empirical measures of spatial continuity for two-dimensional spatial data.
    PDF (5.36MB)  |   HTML


More about This Product Feedback

SAS/STAT 12.1 User's Guide - Procedures

For the complete SAS/STAT 12.1 User's Guide, go to the SAS/STAT product documentation page.

  • The ACECLUS Procedure
    Obtains approximate estimates of the pooled within-cluster covariance matrix when the clusters are assumed to be multivariate normal with equal covariance matrices.
    PDF (10.1MB)  |   HTML
  • The ADAPTIVEREG Procedure (Experimental)
    Fits multivariate adaptive regression splines.
    PDF (11.9MB)  |   HTML
  • The ANOVA Procedure
    Performs analysis of variance for balanced data.
    PDF (9.99MB)  |   HTML
  • The BOXPLOT Procedure
    Creates side-by-side box-and-whiskers plots of measurements organized in groups.
    PDF (10.4MB)  |   HTML
  • The CALIS Procedure
    Fits structural equation models.
    PDF (12.2MB)  |   HTML
  • The CANCORR Procedure
    Performs canonical correlation, partial canonical correlation, and canonical redundancy analysis.
    PDF (9.86MB)  |   HTML
  • The CANDISC Procedure
    Performs a canonical discriminant analysis, computes squared Mahalanobis distances between class means, and performs both univariate and multivariate one-way analyses of variance.
    PDF (10MB)  |   HTML
  • The CATMOD Procedure
    Performs categorical data modeling of data that can be represented by a contingency table.
    PDF (10.1MB)  |   HTML
  • The CLUSTER Procedure
    Hierarchically clusters the observations in a SAS data.
    PDF (12.1MB)  |   HTML
  • The CORRESP Procedure
    Performs simple correspondence analysis and multiple correspondence analysis (MCA).
    PDF (10.3MB)  |   HTML
  • The DISCRIM Procedure
    Develops a discriminant criterion to classify each observation into groups.
    PDF (11.6MB)  |   HTML
  • The DISTANCE Procedure
    Computes various measures of distance, dissimilarity, or similarity between the observations (rows) of a SAS data set. Proximity measures are stored as a lower triangular matrix or a square matrix in an output data set that can then be used as input to the CLUSTER, MDS, and MODECLUS procedures.
    PDF (10.3MB)  |   HTML
  • The FACTOR Procedure
    Performs a variety of common factor and component analyses and rotations.
    PDF (10.5MB)  |   HTML
  • The FASTCLUS Procedure
    Performs a disjoint cluster analysis on the basis of distances computed from one or more quantitative variables.
    PDF (10.4MB)  |   HTML
  • The FMM Procedure
    Fits finite mixture models.
    PDF (11MB)  |   HTML
  • The FREQ Procedure
    Produces one-way to n-way frequency and contingency (crosstabulation) tables and performs table analysis.
    PDF (10.9MB)  |   HTML
  • The GAM Procedure
    Fits generalized additive models.
    PDF (10.7MB)  |   HTML
  • The GENMOD Procedure
    Fits generalized linear models.
    PDF (12MB)  |   HTML
  • The GLIMMIX Procedure
    Fits generalized linear mixed models.
    PDF (13.7MB)  |   HTML
  • The GLM Procedure
    Fits general linear models.
    PDF (11.4MB)  |   HTML
  • The GLMMOD Procedure
    Constructs the design matrix for a general linear model; it essentially constitutes the model-building front end for the GLM procedure.
    PDF (9.8MB)  |   HTML
  • The GLMPOWER Procedure
    Performs prospective power and sample size analysis for linear models.
    PDF (10.7MB)  |   HTML
  • The GLMSELECT Procedure
    Performs effect selection in the framework of general linear models.
    PDF (12.5MB)  |   HTML
  • The HPMIXED Procedure
    Fits linear mixed models with simple covariance component structures by sparse-matrix techniques.
    PDF (10.2MB)  |   HTML
  • The INBREED Procedure
    Calculates the covariance or inbreeding coefficients for a pedigree.
    PDF (9.9MB)  |   HTML
  • The KDE Procedure
    Performs univariate and bivariate kernel density estimation.
    PDF (11.4MB)  |   HTML
  • The KRIGE2D Procedure
    Performs ordinary kriging in two dimensions.
    PDF (14.7MB)  |   HTML
  • The LATTICE Procedure
    Performs analysis of variance and analysis of simple covariance for data from experiments with lattice designs.
    PDF (9.8MB)  |   HTML
  • The LIFEREG Procedure
    Fits parametric models to failure time data that can be uncensored, right censored, left censored, or interval censored.
    PDF (11.3MB)  |   HTML
  • The LIFETEST Procedure
    Computes nonparametric estimates of the survivor function either by the product-limit method (also called the Kaplan-Meier method) or by the lifetable method (also called the actuarial method).
    PDF (11.2MB)  |   HTML
  • The LOESS Procedure
    Implements a nonparametric method for estimating regression surfaces.
    PDF (12MB)  |   HTML
  • The LOGISTIC Procedure
    Fits regression models with binary, ordinal, or nominal dependent variables.
    PDF (12.5MB)  |   HTML
  • The MCMC Procedure
    Performs general-purpose Markov chain Monte Carlo (MCMC) simulation designed to fit Bayesian models.
    PDF (13.7MB)  |   HTML
  • The MDS Procedure
    Fits two- and three-way, metric and nonmetric multidimensional scaling models.
    PDF (10.9MB)  |   HTML
  • The MI Procedure
    Performs multiple imputation of missing data.
    PDF (10.6MB)  |   HTML
  • The MIANALYZE Procedure
    Combines the results of the analyses of imputations and generates valid statistical inferences.
    PDF (10MB)  |   HTML
  • The MIXED Procedure
    Fits general linear models with fixed and random effects.
    PDF (11.8MB)  |   HTML
  • The MODECLUS Procedure
    Clusters observations in a SAS data set by using any of several algorithms based on nonparametric density estimates.
    PDF (13.5MB)  |   HTML
  • The MULTTEST Procedure
    Addresses the multiple testing problem by adjusting the p-values from a family of hypothesis tests.
    PDF (10.6MB)  |   HTML
  • The NESTED Procedure
    Performs random-effects analysis of variance for data from an experiment with a nested (hierarchical) structure and classification effects.
    PDF (9.8MB)  |   HTML
  • The NLIN Procedure
    Fits nonlinear regression models.
    PDF (11MB)  |   HTML
  • The NLMIXED Procedure
    Fits mixed models in which the fixed or random effects enter nonlinearly.
    PDF (10.3MB)  |   HTML
  • The NPAR1WAY Procedure
    Performs nonparametric tests for location and scale differences across a one-way classification.
    PDF (10.2MB)  |   HTML
  • The ORTHOREG Procedure
    Fits general linear models by the method of least squares and provides more accurate estimates than other procedures when your data are ill-conditioned.
    PDF (10.0MB)  |   HTML
  • The PHREG Procedure
    Performs regression analysis of survival data based on the Cox proportional hazards model.
    PDF (11.9MB)  |   HTML
  • The PLAN Procedure
    Constructs designs and randomizes plans for factorial experiments.
    PDF (9.8MB)  |   HTML
  • The PLM Procedure
    Performs postfitting statistical analyses.
    PDF (10.2MB)  |   HTML
  • The PLS Procedure
    Performs principal component regression.
    PDF (12.2MB)  |   HTML
  • The POWER Procedure
    Performs prospective power and sample size analyses for a variety of statistical analyses.
    PDF (14.7MB)  |   HTML
  • The Power and Sample Size Application
    PDF (12MB)  |   HTML
  • The PRINCOMP Procedure
    Performs principal component analysis.
    PDF (11.5MB)  |   HTML
  • The PRINQUAL Procedure
    Performs principal component analysis (PCA) of qualitative, quantitative, or mixed data.
    PDF (11.3MB)  |   HTML
  • The PROBIT Procedure
    Calculates maximum likelihood estimates of regression parameters and the natural (or threshold) response rate for quantal response data from biological assays or other discrete event data.
    PDF (10.8MB)  |   HTML
  • The QUANTLIFE Procedure (Experimental)
    Performs quantile regression analysis for survival data.
    PDF (10.5MB)  |   HTML
  • The QUANTREG Procedure
    Fits quantile regression models.
    PDF (12MB)  |   HTML
  • The QUANTSELECT Procedure (Experimental)
    Performs effect selection in the framework of quantile regression.
    PDF (10.2MB)  |   HTML
  • The REG Procedure
    General-purpose procedure for ordinary least squares regression.
    PDF (14.7MB)  |   HTML
  • The ROBUSTREG Procedure
    Provides resistant (stable) results for linear regression models in the presence of outliers.
    PDF (11.6MB)  |   HTML
  • The RSREG Procedure
    Fits quadratic response surface regression models.
    PDF (10.4MB)  |   HTML
  • The SCORE Procedure
    Multiplies values from two SAS data sets, one containing coefficients and the other containing raw data to be scored using the coefficients from the first data set.
    PDF (9.8MB)  |   HTML
  • The SEQDESIGN Procedure
    Designs interim analyses for group sequential clinical trials.
    PDF (14.4MB)  |   HTML
  • The SEQTEST Procedure
    Performs interim analyses for group sequential clinical trials.
    PDF (13.2MB)  |   HTML
  • The SIM2D Procedure
    Produces a spatial simulation for a Gaussian random field with a specified mean and covariance structure in two dimensions by using an LU decomposition technique.
    PDF (11.8MB)  |   HTML
  • The SIMNORMAL Procedure
    Performs conditional and unconditional simulation for a set of correlated normal or Gaussian random variables.
    PDF (9.9MB)  |   HTML
  • The STDIZE Procedure
    Standardizes one or more numeric variables in a SAS data set by subtracting a location measure and dividing by a scale measure.
    PDF (9.9MB)  |   HTML
  • The STDRATE Procedure
    Computes directly standardized rates and risks for study populations.
    PDF (10.7MB)  |   HTML
  • The STEPDISC Procedure
    Given a classification variable and several quantitative variables, the procedure performs a stepwise discriminant analysis to select a subset of the quantitative variables for use in discriminating among the classes.
    PDF (9.8MB)  |   HTML
  • The SURVEYFREQ Procedure
    Produces one-way to n-way frequency and crosstabulation tables from complex multistage survey designs with stratification, clustering, and unequal weighting.
    PDF (10.3MB)  |   HTML
  • The SURVEYLOGISTIC Procedure
    Fits models with binary, ordinal, or nominal dependent variables and incorporates complex survey designs.
    PDF (10.2MB)  |   HTML
  • The SURVEYMEANS Procedure
    Estimate statistics such as means, totals, proportions, quantiles, and ratios from complex multistage survey designs with stratification, clustering, and unequal weighting.
    PDF (10MB)  |   HTML
  • The SURVEYPHREG Procedure
    Performs regression analysis of survival data based on the Cox proportional hazards model for complex survey sample designs.
    PDF (10.1MB)  |   HTML
  • The SURVEYREG Procedure
    Performs linear regression analysis for complex survey sample designs.
    PDF (10.2MB)  |   HTML
  • The SURVEYSELECT Procedure
    Selects simple random samples or selects samples according to a complex multistage sample design that includes stratification, clustering, and unequal probabilities of selection.
    PDF (10MB)  |   HTML
  • The TPSPLINE Procedure
    Provides penalized least squares estimates.
    PDF (11.9MB)  |   HTML
  • The TRANSREG Procedure
    Fits linear models with optimal nonlinear transformations of variables.
    PDF (17.6MB)  |   HTML
  • The TREE Procedure
    Produces a tree diagram, also known as a dendrogram or phenogram, from a data set created by the CLUSTER or VARCLUS procedure that contains the results of hierarchical clustering as a tree structure.
    PDF (10.3MB)  |   HTML
  • The TTEST Procedure
    Performs t tests and computes confidence limits for one sample, paired observations, two independent samples, and the AB/BA crossover design.
    PDF (11.7MB)  |   HTML
  • The VARCLUS Procedure
    Divides a set of numeric variables into disjoint or hierarchical clusters.
    PDF (9.9MB)  |   HTML
  • The VARCOMP Procedure
    Fits general linear models with random effects (with the option of specifying certain effects as fixed).
    PDF (9.9MB)  |   HTML
  • The VARIOGRAM Procedure
    Computes empirical measures of spatial continuity for two-dimensional spatial data.
    PDF (13.1MB)  |   HTML


More about This Product Feedback

SAS/STAT 9.3 User's Guide - Procedures

For the complete SAS/STAT 9.3 User's Guide, go to the SAS/STAT product documentation page.

  • The ACECLUS Procedure
    Obtains approximate estimates of the pooled within-cluster covariance matrix when the clusters are assumed to be multivariate normal with equal covariance matrices.
    PDF (10.1MB)  |   HTML
  • The ANOVA Procedure
    Performs analysis of variance for balanced data.
    PDF (10.1MB)  |   HTML
  • The BOXPLOT Procedure
    Creates side-by-side box-and-whiskers plots of measurements organized in groups.
    PDF (10.7MB)  |   HTML
  • The CALIS Procedure
    Fits structural equation models.
    PDF (12.5MB)  |   HTML
  • The CANCORR Procedure
    Performs canonical correlation, partial canonical correlation, and canonical redundancy analysis.
    PDF (9.92MB)  |   HTML
  • The CANDISC Procedure
    Performs a canonical discriminant analysis, computes squared Mahalanobis distances between class means, and performs both univariate and multivariate one-way analyses of variance.
    PDF (10MB)  |   HTML
  • The CATMOD Procedure
    Performs categorical data modeling of data that can be represented by a contingency table.
    PDF (10.3MB)  |   HTML
  • The CLUSTER Procedure
    Hierarchically clusters the observations in a SAS data.
    PDF (12.2MB)  |   HTML
  • The CORRESP Procedure
    Performs simple correspondence analysis and multiple correspondence analysis (MCA).
    PDF (10.3MB)  |   HTML
  • The DISCRIM Procedure
    Develops a discriminant criterion to classify each observation into groups.
    PDF (11.7MB)  |   HTML
  • The DISTANCE Procedure
    Computes various measures of distance, dissimilarity, or similarity between the observations (rows) of a SAS data set. Proximity measures are stored as a lower triangular matrix or a square matrix in an output data set that can then be used as input to the CLUSTER, MDS, and MODECLUS procedures.
    PDF (10.4MB)  |   HTML
  • The FACTOR Procedure
    Performs a variety of common factor and component analyses and rotations.
    PDF (10.6MB)  |   HTML
  • The FASTCLUS Procedure
    Performs a disjoint cluster analysis on the basis of distances computed from one or more quantitative variables.
    PDF (10.4MB)  |   HTML
  • The FMM Procedure (Experimental)
    Fits finite mixture models.
    PDF (11.1MB)  |   HTML
  • The FREQ Procedure
    Produces one-way to n-way frequency and contingency (crosstabulation) tables and performs table analysis.
    PDF (11.2MB)  |   HTML
  • The GAM Procedure
    Fits generalized additive models.
    PDF (10.7MB)  |   HTML
  • The GENMOD Procedure
    Fits generalized linear models.
    PDF (12.3MB)  |   HTML
  • The GLIMMIX Procedure
    Fits generalized linear mixed models.
    PDF (14.36MB)  |   HTML  |   Purchase chapter
  • The GLM Procedure
    Fits general linear models.
    PDF (11.8MB)  |   HTML
  • The GLMMOD Procedure
    Constructs the design matrix for a general linear model; it essentially constitutes the model-building front end for the GLM procedure.
    PDF (9.84MB)  |   HTML
  • The GLMPOWER Procedure
    Performs prospective power and sample size analysis for linear models.
    PDF (10.8MB)  |   HTML
  • The GLMSELECT Procedure
    Performs effect selection in the framework of general linear models.
    PDF (12.6MB)  |   HTML
  • The HPMIXED Procedure
    Fits linear mixed models with simple covariance component structures by sparse-matrix techniques.
    PDF (10.3MB)  |   HTML
  • The INBREED Procedure
    Calculates the covariance or inbreeding coefficients for a pedigree.
    PDF (9.92B)  |   HTML
  • The KDE Procedure
    Performs univariate and bivariate kernel density estimation.
    PDF (11.4MB)  |   HTML
  • The KRIGE2D Procedure
    Performs ordinary kriging in two dimensions.
    PDF (14.9MB)  |   HTML
  • The LATTICE Procedure
    Performs analysis of variance and analysis of simple covariance for data from experiments with lattice designs.
    PDF (9.8MB)  |   HTML
  • The LIFEREG Procedure
    Fits parametric models to failure time data that can be uncensored, right censored, left censored, or interval censored.
    PDF (11.2MB)  |   HTML
  • The LIFETEST Procedure
    Computes nonparametric estimates of the survivor function either by the product-limit method (also called the Kaplan-Meier method) or by the lifetable method (also called the actuarial method).
    PDF (11.2MB)  |   HTML
  • The LOESS Procedure
    Implements a nonparametric method for estimating regression surfaces.
    PDF (12.0MB)  |   HTML
  • The LOGISTIC Procedure
    Fits regression models with binary, ordinal, or nominal dependent variables.
    PDF (12.8MB)  |   HTML
  • The MCMC Procedure
    Performs general-purpose Markov chain Monte Carlo (MCMC) simulation designed to fit Bayesian models.
    PDF (14.3MB)  |   HTML
  • The MDS Procedure
    Fits two- and three-way, metric and nonmetric multidimensional scaling models.
    PDF (11.0MB)  |   HTML
  • The MI Procedure
    Performs multiple imputation of missing data.
    PDF (10.7MB)  |   HTML
  • The MIANALYZE Procedure
    Combines the results of the analyses of imputations and generates valid statistical inferences.
    PDF (9.98MB)  |   HTML
  • The MIXED Procedure
    Fits general linear models with fixed and random effects.
    PDF (12.26MB)  |   HTML  |   Purchase chapter
  • The MODECLUS Procedure
    Clusters observations in a SAS data set by using any of several algorithms based on nonparametric density estimates.
    PDF (13.6MB)  |   HTML
  • The MULTTEST Procedure
    Addresses the multiple testing problem by adjusting the p-values from a family of hypothesis tests.
    PDF (10.7MB)  |   HTML
  • The NESTED Procedure
    Performs random-effects analysis of variance for data from an experiment with a nested (hierarchical) structure and classification effects.
    PDF (9.84MB)  |   HTML
  • The NLIN Procedure
    Fits nonlinear regression models.
    PDF (10.8MB)  |   HTML
  • The NLMIXED Procedure
    Fits mixed models in which the fixed or random effects enter nonlinearly.
    PDF (10.4MB)  |   HTML
  • The NPAR1WAY Procedure
    Performs nonparametric tests for location and scale differences across a one-way classification.
    PDF (10.2MB)  |   HTML
  • The ORTHOREG Procedure
    Fits general linear models by the method of least squares and provides more accurate estimates than other procedures when your data are ill-conditioned.
    PDF (10.0MB)  |   HTML
  • The PHREG Procedure
    Performs regression analysis of survival data based on the Cox proportional hazards model.
    PDF (12.0MB)  |   HTML
  • The PLAN Procedure
    Constructs designs and randomizes plans for factorial experiments.
    PDF (9.91MB)  |   HTML
  • The PLM Procedure
    Performs postfitting statistical analyses.
    PDF (10.3MB)  |   HTML
  • The PLS Procedure
    Performs principal component regression.
    PDF (12.3MB)  |   HTML
  • The POWER Procedure
    Performs prospective power and sample size analyses for a variety of statistical analyses.
    PDF (15.3MB)  |   HTML
  • The Power and Sample Size Application
    PDF (12.2MB)  |   HTML
  • The PRINCOMP Procedure
    Performs principal component analysis.
    PDF (11.9MB)  |   HTML
  • The PRINQUAL Procedure
    Performs principal component analysis (PCA) of qualitative, quantitative, or mixed data.
    PDF (11.2MB)  |   HTML
  • The PROBIT Procedure
    Calculates maximum likelihood estimates of regression parameters and the natural (or threshold) response rate for quantal response data from biological assays or other discrete event data.
    PDF (10.9MB)  |   HTML
  • The QUANTREG Procedure
    Fits quantile regression models.
    PDF (12.0MB)  |   HTML
  • The REG Procedure
    General purpose procedure for ordinary least squares regression.
    PDF (14.7MB)  |   HTML  |   Purchase chapter
  • The ROBUSTREG Procedure
    Provides resistant (stable) results for linear regression models in the presence of outliers.
    PDF (11.7MB)  |   HTML
  • The RSREG Procedure
    Fits quadratic response surface regression models.
    PDF (10.4MB)  |   HTML
  • The SCORE Procedure
    Multiplies values from two SAS data sets, one containing coefficients and the other containing raw data to be scored using the coefficients from the first data set.
    PDF (9.88MB)  |   HTML
  • The SEQDESIGN Procedure
    Designs interim analyses for group sequential clinical trials.
    PDF (14.5MB)  |   HTML
  • The SEQTEST Procedure
    Performs interim analyses for group sequential clinical trials.
    PDF (13.0MB)  |   HTML
  • The SIM2D Procedure
    Produces a spatial simulation for a Gaussian random field with a specified mean and covariance structure in two dimensions by using an LU decomposition technique.
    PDF (11.9MB)  |   HTML
  • The SIMNORMAL Procedure
    Performs conditional and unconditional simulation for a set of correlated normal or Gaussian random variables.
    PDF (9.92MB)  |   HTML
  • The STDIZE Procedure
    Standardizes one or more numeric variables in a SAS data set by subtracting a location measure and dividing by a scale measure.
    PDF (9.98MB)  |   HTML
  • The STEPDISC Procedure
    Given a classification variable and several quantitative variables, the procedure performs a stepwise discriminant analysis to select a subset of the quantitative variables for use in discriminating among the classes.
    PDF (9.87MB)  |   HTML
  • The SURVEYFREQ Procedure
    Produces one-way to n-way frequency and crosstabulation tables from complex multistage survey designs with stratification, clustering, and unequal weighting.
    PDF (10.5MB)  |   HTML
  • The SURVEYLOGISTIC Procedure
    Fits models with binary, ordinal, or nominal dependent variables and incorporates complex survey designs.
    PDF (10.3MB)  |   HTML
  • The SURVEYMEANS Procedure
    Estimate statistics such as means, totals, proportions, quantiles, and ratios from complex multistage survey designs with stratification, clustering, and unequal weighting.
    PDF (10.1MB)  |   HTML
  • The SURVEYPHREG Procedure
    Performs regression analysis of survival data based on the Cox proportional hazards model for complex survey sample designs.
    PDF (10.3MB)  |   HTML
  • The SURVEYREG Procedure
    Performs linear regression analysis for complex survey sample designs.
    PDF (10.3MB)  |   HTML
  • The SURVEYSELECT Procedure
    Selects simple random samples or selects samples according to a complex multistage sample design that includes stratification, clustering, and unequal probabilities of selection.
    PDF (10.2MB)  |   HTML
  • The TPSPLINE Procedure
    Provides penalized least squares estimates.
    PDF (12.0MB)  |   HTML
  • The TRANSREG Procedure
    Fits linear models with optimal nonlinear transformations of variables.
    PDF (18.1MB)  |   HTML
  • The TREE Procedure
    Produces a tree diagram, also known as a dendrogram or phenogram, from a data set created by the CLUSTER or VARCLUS procedure that contains the results of hierarchical clustering as a tree structure.
    PDF (10.5MB)  |   HTML
  • The TTEST Procedure
    Performs t tests and computes confidence limits for one sample, paired observations, two independent samples, and the AB/BA crossover design.
    PDF (11.9MB)  |   HTML
  • The VARCLUS Procedure
    Divides a set of numeric variables into disjoint or hierarchical clusters.
    PDF (9.95MB)  |   HTML
  • The VARCOMP Procedure
    Fits general linear models with random effects (with the option of specifying certain effects as fixed).
    PDF (9.95MB)  |   HTML
  • The VARIOGRAM Procedure
    Computes empirical measures of spatial continuity for two-dimensional spatial data.
    PDF (3.15MB)  |   HTML


More about This Product Feedback

SAS/STAT 9.22 User's Guide - Procedures

For the complete SAS/STAT 9.22 User's Guide, go to the SAS/STAT product documentation page.

  • The ACECLUS Procedure
    PDF (10.2MB)  |   HTML
  • The ANOVA Procedure
    PDF (13.0MB)  |   HTML
  • The BOXPLOT Procedure
    PDF (10.6MB)  |   HTML
  • The CALIS Procedure
    PDF (12.5MB)  |   HTML
  • The CANCORR Procedure
    PDF (9.9MB)  |   HTML
  • The CANDISC Procedure
    PDF (10.1MB)  |   HTML
  • The CATMOD Procedure
    PDF (10.4MB)  |   HTML
  • The CLUSTER Procedure
    PDF (12.5MB)  |   HTML
  • The CORRESP Procedure
    PDF (10.4MB)  |   HTML
  • The DISCRIM Procedure
    PDF (11.7MB)  |   HTML
  • The DISTANCE Procedure
    PDF (10.5MB)  |   HTML
  • The FACTOR Procedure
    PDF (10.7MB)  |   HTML
  • The FASTCLUS Procedure
    PDF (10.4MB)  |   HTML
  • The FREQ Procedure
    PDF (11.0MB)  |   HTML
  • The GAM Procedure
    PDF (10.8MB)  |   HTML
  • The GENMOD Procedure
    PDF (12.3MB)  |   HTML
  • The GLIMMIX Procedure
    PDF (14.2MB)  |   HTML
  • The GLM Procedure
    PDF (11.8MB)  |   HTML
  • The GLMMOD Procedure
    PDF (9.8MB)  |   HTML
  • The GLMPOWER Procedure
    PDF (10.5MB)  |   HTML
  • The GLMSELECT Procedure
    PDF (12.6MB)  |   HTML
  • The HPMIXED Procedure (Experimental)
    PDF (10.3MB)  |   HTML
  • The INBREED Procedure
    PDF (9.9MB)  |   HTML
  • The KDE Procedure
    PDF (11.4MB)  |   HTML
  • The KRIGE2D Procedure
    PDF (14.7MB)  |   HTML
  • The LATTICE Procedure
    PDF (9.8MB)  |   HTML
  • The LIFEREG Procedure
    PDF (11.2MB)  |   HTML
  • The LIFETEST Procedure
    PDF (11.2B)  |   HTML
  • The LOESS Procedure
    PDF (11.9MB)  |   HTML
  • The LOGISTIC Procedure
    PDF (12.8B)  |   HTML
  • The MCMC Procedure
    PDF (14.0MB)  |   HTML
  • The MDS Procedure
    PDF (11.0MB)  |   HTML
  • The MI Procedure
    PDF (10.4MB)  |   HTML
  • The MIANALYZE Procedure
    PDF (10.0MB)  |   HTML
  • The MIXED Procedure
    PDF (12.3MB)  |   HTML
  • The MODECLUS Procedure
    PDF (13.6MB)  |   HTML
  • The MULTTEST Procedure
    PDF (10.7MB)  |   HTML
  • The NESTED Procedure
    PDF (9.8MB)  |   HTML
  • The NLIN Procedure
    PDF (10.5MB)  |   HTML
  • The NLMIXED Procedure
    PDF (10.4MB)  |   HTML
  • The NPAR1WAY Procedure
    PDF (10.3MB)  |   HTML
  • The ORTHOREG Procedure
    PDF (10.0MB)  |   HTML
  • The PHREG Procedure
    PDF (12.0MB)  |   HTML
  • The PLAN Procedure
    PDF (9.9MB)  |   HTML
  • The PLM Procedure
    PDF (10.3MB)  |   HTML
  • The PLS Procedure
    PDF (12.1MB)  |   HTML
  • The POWER Procedure
    PDF (14.2MB)  |   HTML
  • The Power and Sample Size Application
    PDF (12.2MB)  |   HTML
  • The PRINCOMP Procedure
    PDF (11.9B)  |   HTML
  • The PRINQUAL Procedure
    PDF (11.3MB)  |   HTML
  • The PROBIT Procedure
    PDF (11.3B)  |   HTML
  • The QUANTREG Procedure
    PDF (12.0MB)  |   HTML
  • The REG Procedure
    PDF (15.1MB)  |   HTML
  • The ROBUSTREG Procedure
    PDF (11.6MB)  |   HTML
  • The RSREG Procedure
    PDF (10.4MB)  |   HTML
  • The SCORE Procedure
    PDF (9.9MB)  |   HTML
  • The SEQDESIGN Procedure
    PDF (14.3MB)  |   HTML
  • The SEQTEST Procedure
    PDF (13.0MB)  |   HTML
  • The SIM2D Procedure
    PDF (11.8MB)  |   HTML
  • The SIMNORMAL Procedure
    PDF (9.9MB)  |   HTML
  • The STDIZE Procedure
    PDF (10.0MB)  |   HTML
  • The STEPDISC Procedure
    PDF (9.9MB)  |   HTML
  • The SURVEYFREQ Procedure
    PDF (10.5MB)  |   HTML
  • The SURVEYLOGISTIC Procedure
    PDF (10.4MB)  |   HTML
  • The SURVEYMEANS Procedure
    PDF (10.2MB)  |   HTML
  • The SURVEYPHREG Procedure
    PDF (10.3MB)  |   HTML
  • The SURVEYREG Procedure
    PDF (10.4MB)  |   HTML
  • The SURVEYSELECT Procedure
    PDF (10.2MB)  |   HTML
  • The TPSPLINE Procedure
    PDF (11.8MB)  |   HTML
  • The TRANSREG Procedure
    PDF (18.2MB)  |   HTML
  • The TREE Procedure
    PDF (10.0MB)  |   HTML
  • The TTEST Procedure
    PDF (11.8MB)  |   HTML
  • The VARCLUS Procedure
    PDF (10.0MB)  |   HTML
  • The VARCOMP Procedure
    PDF (9.9MB)  |   HTML
  • The VARIOGRAM Procedure
    PDF (13.4MB)  |   HTML