Data Analysis Examples

The pages below contain examples (often hypothetical) illustrating the application of different statistical analysis techniques using different statistical packages. Each page provides a handful of examples of when the analysis might be used along with sample data, an example analysis and an explanation of the output, followed by references for more information. These pages merely introduce the essence of the technique and do not provide a comprehensive description of how to use it.

The combination of topics and packages reflect questions that are often asked in our statistical consulting. As such, this heavily reflects the demand from our clients at walk in consulting, not demand of readers from around the world. Many worthy topics will not be covered because they are not reflected in questions by our clients. Also, not all analysis techniques will be covered in all packages, again largely determined by client demand. If an analysis is not shown in a particular package,this does not imply that the package cannot do the analysis, it may simply mean that the analysis is not commonly done in that package by our clients.

Stata SAS SPSS Mplus R
Regression Models
Robust Regression Stata SAS R
Models for Binary and Categorical Outcomes
Logistic Regression Stata SAS SPSS Mplus R
Exact Logistic Regression Stata SAS R
Multinomial Logistic Regression Stata SAS SPSS Mplus R
Ordinal Logistic Regression Stata SAS SPSS Mplus R
Probit Regression Stata SAS SPSS Mplus R
Count Models
Poisson Regression Stata SAS SPSS Mplus R
Negative Binomial Regression Stata SAS SPSS Mplus R
Zero-inflated Poisson Regression Stata SAS Mplus R
Zero-inflated Negative Binomial Regression Stata SAS Mplus R
Zero-truncated Poisson Stata SAS R
Zero-truncated Negative Binomial Stata SAS Mplus R
Censored and Truncated Regression
Tobit Regression Stata SAS Mplus R
Truncated Regression Stata SAS R
Interval Regression Stata SAS R
Multivariate Analysis
One-way MANOVA Stata SAS SPSS
Discriminant Function Analysis Stata SAS SPSS
Canonical Correlation Analysis Stata SAS SPSS R
Multivariate Multiple Regression Stata SAS Mplus
Mixed Effects Models
Generalized Linear Mixed Models Introduction to GLMMs
Mixed Effects Logistic Regression Stata R
Other
Latent Class Analysis Mplus

Power Analyses

For grants and proposals, it is also useful to have power analyses corresponding to common data analyses. We have examples of some simple power analyses below.

Stata SAS SPSS Mplus R G*Power
Power Analysis / Sample Size
Single-sample t-test Stata SAS R G*Power
Paired-sample t-test Stata SAS R G*Power
Independent-sample t-test Stata SAS R G*Power
Two Independent Proportions Stata SAS G*Power
One-way ANOVA Stata SAS G*Power
Multiple Regression Stata SAS G*Power
Accuracy in Parameter Estimation Stata

How to cite this page

Report an error on this page or leave a comment

The content of this web site should not be construed as an endorsement of any particular web site, book, or software product by the University of California.