Introduction to SAS

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Note: Topic order is subject to change. Participants must sign up for the all sessions.

Fundamentals: This portion introduces SAS for Windows environment, creating and submitting command files, printing output and simple trouble shooting techniques. Basics of how to read in raw data from different types of files are covered. Simple methods for data checking also are demonstrated.

Transformations and Recodes: This portion introduces the use of SAS to create new variables using formulas, recoding continuous variables into categories, creating dummy variables, the use of dates in SAS and defining missing values.

Data Management: This portion covers how to create and read permanent SAS datasets, basics of how to combine SAS data sets, both to add cases and to add variables.

Importing Data: This portion introduces the basics of importing data from other programs, such as Excel, Access and SPSS into SAS. Guidelines for preparing data for use with other programs are covered.

Introduction to Programming in Stata

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Note: Topic order is subject to change. Participants must sign up for all the sessions. Please note the course prerequisites below.

This workshop introduces participants to programming in Stata. The workshop will cover many of Stata’s commands designed to make repetitive tasks easier. Topics such as indexing, looping, using calculated results, macros, and the creation of programs will be covered and these concepts will be taught through many hands-on exercises.  Familiarity with Stata is suggested. The workshop will be conducted using Stata for Windows.

Topics include:

  • Interactive and mechanical programming modes
  • Understanding the difference between Stata .do files, programs and .ado files
  • Indexing
  • Looping and branching
  • Local macros
  • Debugging tools
  • Using Stata’s calculated results stored in r() and e()
  • Getting started with programs and .ado files

Intermediate Topics in SPSS: Advanced Statistical Models

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Note: This is a companion workshop of “Intermediate Topics in SPSS: Data Management and Macros,” and participants may register for one or both days.

This two-half-days workshop is designed to provide experienced SPSS users (see prerequisites below) with hands-on exposure to more advanced statistical analysis techniques in SPSS, using SPSS for Windows.

The workshop will cover the following topics at a moderate pace: General Linear Models, Repeated Measures Analysis of Variance (ANOVA), Linear Mixed Models / Hierarchical Linear Models, and Generalized Linear Mixed Models. There will also be time for an open discussion of participant issues with analyzing data in SPSS.

Regression Analysis

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This workshop will provide participants with an overview of commonly used methods in simple linear regression and multiple linear regressions. There will be both lecture and hands-on computer work, using SPSS. Topics will include: the basic regression model, model assumptions, interpretation of coefficients, significance testing, interactions between variables and the use and interpretation of dummy variables. Model checking methods, including residual plots, collinearity diagnostics, and influence plots will also be covered. Several methods for model selection, including all possible regressions and stepwise selection will be included.

Statistical Analysis with R

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This workshop will introduce participants to R. R is a free and open source environment for data analysis and statistical computing.  While R contains many built-in statistical procedures, the most unique feature of R is the facility for users to extend these procedures to suit their own needs.  Excellent graphics are another reason R is gaining wide popularity.

  • How to Obtain R
  • Help Tools
  • Importing / Exporting Data
  • Data Management
  • Descriptive Statistics
  • Multivariate Statistical Analyses (Regression Modeling, ANOVA, etc.)
  • Graphics
  • Creating Functions

Applied Structural Equation Modeling

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This workshop will help participants develop skills in defining, estimating and testing plausible structural equation models. Attention will be paid to SEM submodels (path analysis and confirmatory factor analysis) as well as full structural equation models. Latent growth curves and multiple group analyses will also be introduced along with generalized structural equation models. This workshop is intended to be an introduction to structural equation modeling and will be conducted using Stata for Windows. Prior experience with Stata is not necessary and all of the concepts discussed in the workshop can be applied in other statistical software packages.