Date: Tue, 16 Mar 2004 12:35:50 -0500
Reply-To: "Schechter, Robert S" <robert.schechter@ASTRAZENECA.COM>
Sender: "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From: "Schechter, Robert S" <robert.schechter@ASTRAZENECA.COM>
Subject: Re: List of statistical procs
Content-Type: text/plain; charset="iso-8859-1"
I got this from <http://filebox.vt.edu/cc/sas/statproc.html>
The following procedures are documented in SAS/STAT User's Guide Vols. I&II
ACECLUS obtains approximate estimates of the pooled within-cluster
covariance matrix when the clusters can be assumed to be multivariate normal
with equal covariance matrices.
ANOVA performs analysis of variance for balanced data from a wide variety of
experimental designs.
CALIS estimates parameters and tests the appropriateness of linear
structural equation models using covariance structure analysis.
CANCORR performs canonical correlation, partial canonical correlation, and
canonical redundancy analysis. The CANCORR procedure can create output data
sets containing canonical coefficients and scores on canonical variables.
CANDISC performs a canonical discriminant analysis, computes squared
Mahalanobis distances, and does both univariate and multivariate one-way
analysis of variance.
CATMOD a procedure for CATegorical data MODeling. PROC CATMOD analyzes data
that can be represented by a contingency table. It fits linear models to
functions of response frequencies and can be used for linear modeling,
loglinear modeling, logistic regression, and repeated measurement analysis.
CLUSTER hierarchically clusters the observations in a SAS data set using one
of 11 methods. The data can be numeric coordinates or distances.
CORRESP performs simple and multiple correspondence analyses.
DISCRIM computes various discriminant functions for classifying observations
into tow or more groups on the basis of one or more quantitative variables.
FACTOR performs several types of common factor and component analysis.
FASTCLUS designed for disjoint clustering of very large data sets and can
find good clusters with only two or three passes over the data.
FREQ produces one-way to n-way frequency and crosstabulation tables.
GLM uses the method of least squares to fit general linear models. Among the
statistical methods available in PROC GLM are regression, analysis of
variance, analysis of covariance, multivariate analysis of variance, and
partial correlation.
LIFEREG fits parametric models to failure time data that may be right-,
left-, or interval-censored.
LIFETEST can be used with data that may be right-censored to compute
nonparametric estimates of the survival distribution and to compute rank
tests for association of the response variable with other variables.
LOGISTIC fits linear logistic regression models for binary or ordinal
response data by the method of maximum likelihood.
NESTED performs random effects analysis of variance and covariance for data
from an experiment with a nested (hierarchical) structure.
NLIN computes least squares or weighted least squares estimates of the
parameters of a nonlinear model.
NPAR1WAY performs analysis of variance on ranks, and it computes several
statistics based on the empirical distribution function and certain rank
scores of a response variable across a one-way classification.
ORTHOREG performs regression using the Gentleman-Givens method.
PLAN constructs, designs, and randomizes plans for nested and crossed
experiments.
PRINCOMP performs principal component analysis.
PRINQUAL obtains linear and nonlinear transformations of variables using the
method of alternating least squares to optimize properties of the
transformed variables covariance or correlation matrix.
PROBIT calculates maximum-likelihood estimates of regression parameters and
natural (threshold) response rate for biological quantal assay response data
or other discrete event data.
REG fits linear regression models by least-squares.
RSREG fits the parameters of a complete quadratic response surface and
analyzes the fitted surface to determine the factor levels of optimum
response.
SCORE 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.
STEPDISC performs a stepwise discriminant analysis by forward, backward
elimination, or stepwise selection of quantitative variables that can be
useful for discriminating among several classes.
TRANSREG obtains linear and nonlinear transformations of variables using the
method of alternating least squares to fit the data to linear, canonical
correlation, and analysis-of-variance.
TREE prints a tree diagram, also known as a dendrogram or phenogram, using a
data set created by the CLUSTER or VARCLUS procedure.
TTEST performs a two sample t-test for testing the hypothesis that the means
of two groups of independent and normally distributed observations are
equal.
VARCLUS performs either disjoint or hierarchical clustering of variables
based on a correlation or covariance matrix.
VARCOMP estimates the variance components in a general linear model.
Virginia Tech Computing Center--Distributed Information Systems
Last updated: October 31, 1995
-----Original Message-----
From: Peter Flom [mailto:flom@NDRI.ORG]
Sent: Tuesday, March 16, 2004 12:02 PM
To: SAS-L@LISTSERV.UGA.EDU
Subject: List of statistical procs
Does anyone know if there is a list of all the statistical procs in some
format that can be read by Word or Excel?
The reason I ask is that our local group (NYASUG) is interested in
doing a survey about these PROCs
TIA
Peter
Peter L. Flom, PhD
Assistant Director, Statistics and Data Analysis Core
Center for Drug Use and HIV Research
National Development and Research Institutes
71 W. 23rd St
www.peterflom.com
New York, NY 10010
(212) 845-4485 (voice)
(917) 438-0894 (fax)
