A statistical analysis project for the Connection

Description:

This is a statistical analysis research project on Analyzing Client Behavior in The Connection, sponsored by the Connection Inc. and Wesleyan Quantitative Analysis Center.

Authors:

• Jiner Zheng 🐤, Keli Jiang 🦦 , Leah Ewers 🤸‍♀️

• Faculty Advisor: Professor Jennifer Rose

Research Questions:

1. Where do The Connection clients locate to after the programs and what are their characteristics?

2. What social and psychological factors are associated with an increased likelihood of behavioral incidents during clients' participation in Connection programming?

Useful Code Sources:

• first_report.Rmd contains code for data cleaning, data management, univariate analyses, & regression modeling.

• latent-class-analysis.Rmd contains code for performing LCA on sub-sample.

• LCA-report&chi.Rmd contains code for EDA of client class profiles and chi-square tests.

Note: you can also set up the environment using stat-consulting.Rproj in R.

Output & Materials:

• #Team1-Presentation.pptx contains our presentation slides outlining our measures, analytical methods, findings, and recommendations.

• LCA-output.html contains output of the Latent Class Analysis.

• LCA-report&chi.html contains exploratory analyses of client profiles and chi-square test results.

• client_class.csv contains data of complete client profiles with the latent class membership (on the sub-sample used in LCA).