Analyzing surveys

You can visually explore datasets in the Detail View. You can:

• Hide columns to limit the amount of data you are looking at—for example, if you want to see the first column in your dataset next to the fifth column, you can hide the intervening columns.
• Use the sort or filter functions to see patterns in your data. For example, if your dataset contains survey responses and includes a classifying field for sex, you can use the sort or filter functions to view the responses of the males or females.
• Manually code survey responses at codes representing the themes in your data.

You can also run queries to find and code to themes in your data:

• Run a Word Frequency query to identify common themes in the survey responses.
• Run a Text Search query to find all instances of a particular word or phrase.

Gather responses to each question

Do you want to see how all respondents replied to a question? The Survey Import Wizard gathers responses to each open-ended survey question at a code—allowing you to group the data into broad themes.

With all responses to a question grouped to a single code, you can then use some of NVivo's powerful analysis tools to analyze the data.

• Open the code and visually explore content coded to the code. From here you could 'code on' to more granular thematic groupings. For example, you could gather all answers which mentioned car-free zones.
• Run a Word Frequency query (using the code in the scope of the query) to find common words or concepts in responses to Question 4.
• Run a Text Search query looking for particular words or concepts, using the code in the scope of the query. For example, you could search for education and code all the results to a new code.
• Generate a cluster analysis diagram. For example, you can explore the similarity between the responses to Question 4 and responses to other survey questions.
• Open the code, then manually code a portion of the responses to a group of codes (car free zones, lighting, safety barriers), then use pattern-based coding to autocode the code to the specific thematic codes that relate to that question. Automatic coding using existing coding patterns
• Automatically analyze content in the codes to detect themes or sentiment (this requires your installation of NVivo to have coding enhancements). Automated insights

Gather responses of each survey respondent

Survey responses are stored at the cases that represent each respondent. If your data contains closed-ended questions that describe your survey respondents—for example, age and gender—the Wizard creates these as case attributes.

With survey responses coded to cases for each respondent, you can use analysis tools which compare their attribute values. For example:

• Create charts to compare the demographic attributes of your respondents—perhaps your respondents are mostly males under 30 years old?.
• Generate a cluster analysis diagram that compares the attribute values of your respondents—are there clusters of respondents with similar characteristics? Are there any 'outliers'—respondents with demographic characteristics that are very different from the others.
• Run a Word Frequency query (using the case in the scope of the query) to find common words or concepts in responses to Question 4. You could code the results at new codes to further refine your analysis.
• Run a Text Search query looking for particular words or concepts, using the case in the scope of the query. For example, you could search for education and code all the results at a new code.

When survey content is gathered at both question codes (Question 4, Question 5 ) and cases (Anna, Jack, Maria, Peter), you can analyze what respondents in different demographic groups are saying in response to particular questions:

• Use a Coding query to view all the responses of males under 30 years to Question 4.
• Use a Word Frequency query to find the most commonly occurring words or ideas that females mention when responding to Question 5

NOTE  If you have demographic information about your respondents stored separately from your survey data, you may need to set the attribute values by another method. For example, you can import case attribute values from a spreadsheet or by importing from another NVivo project. Classification sheets

Grouping demographic values into ranges

When you use demographic information in the dataset to set attribute values for cases, you can optionally group values into ranges.

For example, if your dataset contains the age of your respondents, it may be more useful to know that an individual participant is within the 21-29 age range, than to know their precise age.

The Classify Cases from Dataset Wizard allows you to the group values. Cases

Autocode survey responses based on existing coding patterns

(This feature is only available in NVivo installations with coding enhancements enabled.)

You can use pattern-based autocoding to speed up the process of coding survey responses. Before you use pattern-based coding, you need to start with manual 'pilot' coding of the responses—for example, code 5-10% of the responses manually.

If your dataset contains responses to questions on a range of topics or issues, you may get better results with pattern-based coding if you autocode the responses to one question at a time using specific thematic codes that relate to that question.

1. First, gather a subset of responses for each question and perform manual 'pilot' coding as follows:
   1. Filter the rows in your dataset to show only the responses you want to use for your pilot coding. For example, you could show the rows prior to a particular response date.
   2. Autocode the dataset using file structure to gather the responses into a code for each question— for example, Question 1, Question 2, Question 3. In step 3 of the Wizard, choose to code Filtered rows only.
   3. Open each question code and manually 'code on' to a group of thematic codes specific to that question.
2. Next, autocode the rest of the responses using existing coding patterns as follows:
   1. Change the filtering in your dataset to hide the responses that were already coded—for example, you could hide rows prior to a particular response date. The reason for filtering the data is to ensure that pattern coding doesn’t re-code responses that you’ve already coded manually.
   2. Again, autocode the dataset using file structure to gather the responses into a new code for each question. In step 3 of the Wizard, choose to code Filtered rows only. In step 5 of the Wizard, create the new codes in a location Under a New Code (so that they are in a separate code hierarchy from the question codes you created for pilot coding).
   3. For each question code in the new code hierarchy, use pattern-based coding to autocode the responses to the specific thematic codes for that question.

If you plan to import multiple times from the same SurveyMonkey survey—for example, by periodically gathering completed responses to an open survey—you can import and manually code the initial responses. Then later, you can import additional responses and use pattern-based autocoding on the new data.

Pattern-based autocoding is an experimental feature that you can test and try out. This feature is designed to speed up the coding process for large volumes of textual content. Automatic coding using existing coding patterns