Discussion: Missing Data

This week’s Learning Resources include several different ways to identify and assess the issue of missing data in your database. From your assessment and knowledge of possible ways to manipulate data, and to overcome potential challenges presented by the missing data, you will be able to analyze and reach conclusions about your analysis. It is important to recognize when and how to apply the most viable solution to the missing data. In addition, it is important to learn to recognize when your data results could be compromised by missing data.

For this Discussion, you will analyze the impact of missing data on data analysis.

To prepare:

• Review this week’s Learning Resources.

By Day 3

Post a 2- to 3-paragraph analysis of missing data. Include the following in your post:

• An explanation of the importance of handling missing data and skipping patterns and how missing data can affect data analysis
• A technique on how you may handle missing data appropriately with an explanation of why this technique works
• Choose one of the variables you selected for your Scholar-Practitioner Project (select one with missing values) and report proportion of missing for that variable
• Indicate the possible reason for the missing values in that variable.

Support your post with the Learning Resources and current literature. Use APA formatting for your Discussion and to cite your resources.

Read a selection of your colleagues’ postings.

By Day 5

Respond to at least one of your colleagues in one or more of the following ways:

• Expand on the colleague’s posting with additional insight and resources.
• Offer polite disagreement or critique, supported with evidence.

In addition, you may also respond as follows:

• Offer and support an opinion.
• Validate an idea with your own experience.
• Make a suggestion or comment that guides or facilitates the discussion.

Support your response with additional scholarly resources. Use APA formatting for your Discussion and to cite your resources.