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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
  • 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

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

See New in Stata 13 for more about what was added in Stata 13.

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