Multivariate Analysis Procedures Available in NCSS

Multivariate analysis refers to a group of statistical techniques that analyze two or more variables at a time, including: discriminant analysis, factor analysis, cluster analysis, logistic regression, MANOVA, and principal component analysis.

Features

Discriminant Analysis
> Canonical coefficients
> Classification reports
> Influential variable reports
> Linear discriminant functions, scores, and coefficients
> Prior probabilities
> Stepwise variable selection

Cluster Algorithms
> Complete linkage
> Dendrograms
> Fuzzy clustering
> Hierarchical
> K-means algorithm
> Medoid partitioning
> Nearest neighbor
> Regression clustering
> Single linkage

Factor and Principal Component Analysis
> Bartlett’s sphericity test
> Communality estimates
> Correlation matrix input
> Eigenvalue/vector analysis
> Factor loadings and scores
> Gleason-Staelin redundancy
> Missing value estimation
> Outlier detection
> Principal axis method
> Quartimax rotation
> Robust estimation
> Score and loading plots
> Scree plot
> T2 analysis
> Varimax rotation

Equality of Covariance
> Bartlett’s variance test
> Box’s M test
> Cronbach's alpha
> Eigenvalue analysis
> Maximum likelihood

MANOVA
> Approximate F-test
> Box’s M test
> Canonical analysis
> Homogeneity of variance test
> Hotelling’s T2
> Lawley-Hotelling trace
> Pillai’s trace
> Roy’s largest root
> Wilks’ lambda

Logistic Regression
> Beta estimates
> Chi-square tests
> Classification table
> Deviance statistics
> Likelihood ratio tests
> Multiple-group dependent variable
> Normal probability plots
> Odds ratios
> Predict new observations
> Residual diagnostics
> Step-down variable selection
> Step-up variable selection

Click here to see more Multivariate procedures available in NCSS.

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NCSS 2007 is now available. This version adds several new procedures and features to NCSS, including mixed models, macros, and an enhanced user interface. Here is a summary of the new procedures, tools, and features:

Procedures
Mixed Models
Circular Data Analysis
Data Matching - Optimal and
Greedy
Data Simulator
Data Stratification
Double Dendrograms
Merging Two Databases
Multiple Regression with Serial
Correlation Correction
Nondetects Analysis
Nondetects Regression

Tools
Macros (Programmability)
Color Selection Windows
Quick Launch Window

Features
Enhanced User Interface
Improved Help System

Read about what’s new in NCSS 2007.

View the upgrade brochure.
View the NCSS 2007 brochure.

Download an NCSS Update

Most Recent NCSS 2007 Update
Released February 19, 2010

What problems have been fixed by recent NCSS updates?

Sample NCSS Reports

Click here for the complete list.

Analysis of Variance
Appraisal Methods
Binary Diagnostic Tests
Charts and Graphs
Cross Tabulation
Curve Fitting
Descriptive Statistics
Design of Experiments
Forecasting
General Linear Models
Meta-Analysis
Multivariate I
Multivariate II
Proportions
Quality Control
Regression Analysis
Reliability Analysis
Repeated Measures
ROC Curves
Survival Analysis
Time Series Analysis
T-Tests


System Requirements PASS 2008, NCSS 2007, and GESS 2006 run on 32-bit and 64-bit systems with Windows 7, Vista, XP, 2000, NT, ME, 98, or 95. Requires pentium-class computer with at least 32 MB of RAM. Requires 200 MB of hard disk space. Requires Adobe Reader® version 7 or later to use the NCSS, PASS, and GESS Help Systems.	Accuracy We at NCSS have put a great deal of effort into finding the most accurate algorithms possible. The programs have been tested and verified over and over, both by us and by our customers. Each routine has been verified against textbooks, journal articles, and, where possible, other software. NCSS is one of the most accurate statistical analysis programs available. NCSS calculates with seventeen-digit, double-precision accuracy.	Guarantee If you are not completely satisfied with an NCSS product during the first 30 days for any reason, return the program for a full, prompt refund (excluding shipping).

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