Other statistical methods

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Other statistical methods

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

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

Additional resource

Base Reference Manual

See New in Stata 18 to learn about what was added in Stata 18.

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