[
Data Screening ||
Matrix Algebra with SAS/IML ||
Regression analysis ||
General Linear Models ||
Canonical correlation, Discriminant analysis ||
Logistic Regression ||
Factor Analysis ||
Clustering and scaling ||
SAS macro programs ||
Data sets ||
Programs]
- calis1.sas
- Testing Equivalence of measures: Lord's Vocabulary Data
Four vocabulary tests are used to test various hypotheses of
equivalence
.
- calis1a.sas
- Lord's data: H4 unconstrained two factor model
A single model is shown represented by both LINEQS statements and by a
path model with RAM statements.
- calis1b.sas
- Testing Equivalence of measures: Lord s Vocabulary Data
Like CALIS1, but also illustrates SAS techniques to extract and combine the
goodness of fit statistics from four different CALIS models.
- calis13.sas
- Ability and Aspiration, LISREL VI, p. III.5
A first-order confirmatory factor model using the data of Calsyn & Kenny (1977).
The model specification is shown using both MATRIX and LINEQS statements.
- calis16.sas
- Nine Psychological Variables, LISREL VI, p. III.106
Several different first-order confirmatory factor analysis models are fit
to the standard 9-variable subset of the Holzinger & Swineford data.
The different models illustrate use of modification indices in model building.
- calis1pow.sas
- Power analysis: Lord's Vocabulary Data (using the CSMPOWER macro)
- calis32.sas
- Vocabulary Test Data, LORD (1957)
- calis33a.sas
- Speed Factor Data, LORD (1956)
A multi-trait (3 kinds of tests) mulit-method (speeded vs. non-speeded) matrix
is analyzed with a confirmatory model specifying both power and speed factors.
- calis36.sas
- Six Different Kinds of Abilties, GUTTMAN (1954)
Two circumplex models are fit to data on 6 ability variables.
- calis65.sas
- CALIS65: Special LISREL Application
- faccorr.sas
- Demonstration of Partial Linear Independence principle.
The factors
account for
the correlations among variables in the sense
that there remain no correlations when the factors are partialled out.
- factor.sas
- Nine Psychological Variables: Harman, page 244
- pca1.sas
- Mean temperature in January and July for selected cities.
Illustrates the ideas of Principal Components analysis for a simple 2-variable problem.
- pca2.sas
- Principal Components analysis of Crime Rates in the U.S.
- phys8.sas
- Eight physical variables
Various exploratory factor solutions are found for 8 physical body measurements,
assumed to measure
lankiness
and stockiness
.
The example also illustrates SAS techniques to input data in the form of a correlation matrix.
- phys8a.sas
- Eight physical variables: Rotation Methods.
- psych9.sas
- Holzinger & Swineford 9 Ability Variables.
- soceco.sas
- Socioeconomic data for 35 countries: PCA.
- spear5.sas
- Spearman's five variables: Harman, Pp 116,391 392