Statistical Analysis Models
You can apply any of the following advanced statistical models to all or some variables in a data set:
- Descriptive statistics: Univariate numeric or graphic summaries
- Categorical data analysis: Cross tabulation
- Event count models, for event count dependent variables:
- Negative binomial regression
- Social network Poisson regression
- Poisson regression
- Models for continuous bounded dependent variables:
- Exponential regression for duration
- Gamma regression for continuous positives
- Log-normal regression for duration
- Social network gamma regression for continuous positives
- Weibull regression for duration
- Models for continuous dependent variables:
- Least squares regression
- Social network least-squares regression
- Social network normal regression
- Linear regression for left-censoreds
- Models for dichotomous dependent variables:
- Logistic regression
- Social network complementary log-log regression
- Social network logistic regression
- Social network probit regression
- Probit regression
- Rare events regression
- Models for ordinal dependent variables:
- Ordinal logistic regression for ordered categoricals
- Ordinal probit regression for ordered categoricals