Cronbach’s alpha

Interitem correlations or covariances

Generate summative scale

Automatically reverse sense of variables

 

Kappa measure of interrater agreement

Two unique raters

Weights for weighting disagreements

Nonunique raters, variables record ratings for each rater

Nonunique raters, variables record frequency of ratings

 

Intraclass correlations

For one-way random-effects models

Individual and average measurements

Absolute agreement

For two-way random-effects models

Individual and average measurements

Absolute agreement

Consistency of agreement

For two-way mixed-effects models

Individual and average measurements

Absolute agreement

Consistency of agreement

 

Stepwise regression

Linear

Beta New

Competing risks

Complementary log-log

Cox

GLM

Interval

Logistic

Conditional logistic

Negative binomial

Ordered logit

Ordered probit

Poisson

Probit

Quantile

Skewed logistic

Tobit

Exponential, Weibull, Gompertz, lognormal, loglogistic, generalized gamma parametric survival

 

 

 

 

Nested model statistics

Wald or likelihood-ratio tests

Use with survey data

 

Kernel-density estimation

Eight different kernels

Control band width

Overlay normal density or Student’s t density

 

Box–Cox transform

Can be applied to the left-hand side, right-hand side, or both

Parameters can be the same or different

Maximum likelihood

Zero-skewness log

 

Power transforms

Search for power transform that converts a variable into a normally distributed variable

Graphical display of a power-transformed variable

 

Orthogonal polynomials

Orthogonalize variables using modified Gram–Schmidt procedures

Compute orthogonal polynomial for a variable

 

Tests of normality

Shapiro–Wilk

Shapiro–Francia

Skewness and kurtosis test (D’Agostino, with and without Royston correction)

Doornik–Hansen

Henze–Zirkler

Two by Mardia

 

Drawing samples from multivariate normal distribution

Default is orthogonal data

May specify desired means and covariance or correlation matrix

Singular covariance matrix is permitted

Set random-number seed to ensure reproducibility

 

Creating datasets with specified correlation structure

Add variables to existing dataset or create new dataset

Singular covariance or correlation structures are permitted

Set random-number seed to ensure reproducibility

 

Collecting statistics into a dataset

Collection from any command

Collection of results for each group or subgroup of observations

Collection from user-written or “official” commands