Advanced Stata

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Note: Topic order is subject to change.  Participants must sign up for the entire series.

This workshop provides additional Stata training on topics more advanced than those covered in the Introduction to Stata workshop. Models for clustered/longitudinal data will be discussed along with other regression modelling techniques such as quantile regression and multinomial logistic regression. Structural Equation Modelling and Survival Analysis in Stata will also be discussed. The workshop will end with an introduction to programming in Stata using .do files. Basic looping techniques and macros will be covered. Note that an entire workshop will be offered in spring term on Programming in Stata. This workshop is designed to teach participants how to implement the methods outlined above in Stata and only a brief overview of the theory behind these methods will be covered. Participants should have a working knowledge of Stata as a prerequisite.

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

Issues in Analysis of Complex Sample Survey Data

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This workshop will provide participants with an introductory, hands-on overview of issues frequently encountered when conducting secondary computer analyses of survey data collected from samples with complex, multi-stage designs (e.g., PSID, NHANES, NCS), including design-based weight determination, software choice, and proper analysis methods.  The workshop is not intended for participants looking to design a survey, but rather for participants who have a desire to analyze complex sample survey data.  Topics to be covered include:

  • Recognizing a sample with a complex design
  • Calculation of sample weights based on sample designs / non-response / post-stratification
  • Calculation of new weights for subgroups / longitudinal analyses
  • Weighted vs. unweighted analyses
  • Calculation of correct confidence intervals for population quantities
  • Hypothesis Testing based on sample estimates
  • Design Effects
  • Software packages capable of complex sample survey data analysis
  • Common analysis methods (linear modeling, descriptive statistics), interpretation of results
  • Approaches to handling missing data using specialized software procedures
  • Hands-on examples using software programs to analyze real survey data

Issues in Analysis of Complex Sample Survey Data

Register
SummaryView full course description

This workshop will provide participants with an introductory, hands-on overview of issues frequently encountered when conducting secondary computer analyses of survey data collected from samples with complex, multi-stage designs (e.g., PSID, NHANES, NCS), including design-based weight determination, software choice, and proper analysis methods.  The workshop is not intended for participants looking to design a survey, but rather for participants who have a desire to analyze complex sample survey data.  Topics to be covered include:

 

  • Recognizing a sample with a complex design
  • Calculation of sample weights based on sample designs / non-response / post-stratification
  • Calculation of new weights for subgroups / longitudinal analyses
  • Weighted vs. unweighted analyses
  • Calculation of correct confidence intervals for population quantities
  • Hypothesis Testing based on sample estimates
  • Design Effects
  • Software packages capable of complex sample survey data analysis
  • Common analysis methods (linear modeling, descriptive statistics), interpretation of results
  • Approaches to handling missing data using specialized software procedures
  • Hands-on examples using software programs to analyze real survey data

 

Applied Structural Equation Modeling

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This workshop is designed to help participants develop skills in defining, estimating and testing structural equation models. Applied Structural Equation Modeling will focus on covariance structure models with latent variables. Two submodels, confirmatory factor analysis and path analysis, will also be covered.  Lectures covering structural equation modeling in general will be interspersed with hands-on computer work. The workshop is intended as an introduction to structural equation modeling. The software used is Stata–no prior use of Stata is required