Back Checks

Back checks of a survey ...

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Purpose

Back checks are done to monitor the quality of the field work. This gives us valuable information on whether the questionnaire accurately captures the key outcomes of the study or not, and on whether the enumerators are explaining the questions as intended.

Best Practices during back checks

Here are some of the best practices that should be done while performing back checks:

• Around 10% of the total survey should be back checked for with 20% of the back checks done in the first 2 weeks of field work.
• Every team and every surveyor must be back checked.
• The back check sample must include proportional number of missing and replacement respondents.
• Households must be selected at random for back checks.

How to Select Back Check Questions

Back check questions should be selected with both the performance of the questionnaire and the surveyor in mind. Using different types of questions during the back check helps in finding the cause of poor data quality. Some of the questions that should be asked during a back check are as follows:

Identifying Respondents and Interview Information

- Check if we have the right person

- Check if they interview took place and when did it take place.

Type 1 Variables

-Straightforward questions where we expect no variation.

-For example - education level, marital status, occupation, has children or not, etc.

Type 2 Variables

- Questions where we expect capable enumerators to get the true answer.

Type 3 Variables

- Questions that we expect to be difficult. We back check these questions to understand if they were correctly interpreted in the field.

The total duration of the back checks should be around 10-15 minutes.

Comparing Back Checks to Actual Survey Data

After completing a back check, you can now compare the data obtained from the back check to your actual survey data to verify whether your data is valid or not. This can be done by using the Stata command bcstats after installing it using ssc install bcstats `.

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This article is part of the topic Monitoring Data Quality

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