Outcomes analysis

The two webinars below presented by Greg Vinson demonstrate the process to examine relationships within your data.  Sample Excel files are provided, with step by step guidance, to perform basic statistical analysis.   These examples show how to make sense of Excel output, and how to write your results in meaningful text.    

In addition you will review steps to evaluate the validity and reliability of your data. These steps will confirm whether your measure accurately represents the construct you are studying.

The process of evidence-based evaluation is also reviewed.

Adapting and Modifying Evidence-Based Practices for Torture Survivor Programs

Joan Othieno discusses how to use quantifiable evidence to identify which practices support your organization’s desired outcomes. She discusses how this evidence-based approach can demonstrate effective delivery of service to clients, and demonstrate how a specific practice produces a desired outcome. The evidence based process was developed within the medical sciences, and can be used as a small-scale approach to outcomes evaluation. She also discusses ways to identify unintended outcomes.

Demonstrating Client Improvement to Yourself and Others Part 2: Understanding and Using your Outcome Evaluation System

Greg Vinson shows how to analyze data, including step by step examples in Excel. (This webinar is part two of a three part series.)  He reviews basic statistical methods to compare means at two points in time, shows how to use Excel to conduct a t-test to identify significant difference, and calculates a Cohen’s d value to examine effect size.   Additional examples include using Chi-Square to see significance between two measures of categorical data (for example percentage of clients showing depression at two points in time) and using Correlation, to identify relationships between variables.

Demonstrating Client Improvement to Yourself and Others Part 3: Making Sure Client Numbers Reflect Client Reality

Greg Vinson discusses the key role that statistical measures plays in showing the success of your program.  (This webinar is part 3 of a three part series.) He reviews basic statistical methods to demonstrate the effectiveness of your program.  He assesses how well a measure represents the reality (the “construct”) you seek to examine.  He shows the need to examine reliability and validity in order to minimize false conclusions. He shows how to calculate a Cronbach’s alpha value within Excel, to examine the internal consistency of your data, and how to interpret the results.