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
- Competing risks
- Complementary log-log
- Cox
- GLM
- Interval
- Interval-censored parametric survival
- Logistic
- Conditional logistic
- Negative binomial
- Ordered logit
- Ordered probit
- Poisson
- Probit
- Quantile
- Skewed logistic
- Tobit
- Exponential, Weibull, Gompertz, lognormal, loglogistic, generalized gamma parametric survival
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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 community-contributed or “official” commands