As a developer, I try to make sure all the most-used features of JMP are where you can find them easily. That’s why the options to change the statistics shown in the crosstab are at the top of Categorical’s red triangle menu. That’s why the new “Redo” and “Save Script” buttons are always in the same spot. But there are always some neat features that I wish I could make more prominent. This blog series will show off a few of them, starting with Aligned Responses.
Many surveys have questions about a person’s attitudes toward different ideas, or their satisfaction with different attributes of a good or service. Most of these are rated on an ordinal scale (e.g., 1-5 where 1 is “Poor”, and 5 is “Excellent”, or 1-5 where 1=”Strongly Disagree” and 5= “Strongly Agree”). Sensory analysis often uses a “Just About Right” (JAR) scale where negative numbers indicate “Not enough” of a particular flavor (Saltiness, Sweetness, etc), positive numbers indicate “Too much” of the flavor, and values near 0 are “Just About Right”.
All of these cases have two features in common: 1) The values have an inherent order, and 2) they are all measured on the same scale. You can use Aligned Responses in the Categorical platform to get a streamlined comparison for many of these columns at once.
Measures of self-perception
As an example, let’s take a look at a famous survey about attitudes and social activities called the “Bowling Alone” data. This data set has a lot of questions that would be good candidates for Aligned Responses. Let’s take a look at a series of questions that measures how people feel about themselves:
People were asked to rate how much they agreed with each of these statements on a scale of 1 (Definitely Disagree) to 6 (Definitely Agree). The way the questions are worded, you can think of these as measures of how people feel about themselves: Do they see themselves as competent? Someone who is respected by others? A resource for friends and neighbors?
It’s interesting to compare these different measures of self-perception. Aligned Responses is tailored for this type of analysis.
Exploring the data
On the Analyze menu, go to Consumer Studies and choose Categorical. By default, the first tab you see is the “Simple” tab (you may see a different one if you’ve set your Preferences). Clicking on the “Related” tab, we see that there are several types of responses JMP considers related, including Aligned Responses, Repeated Measures, and Rater Agreement. They all give the same basic Crosstab and Share Charts, but they report different statistics. See the JMP Consumer Research book for more details.
In our case, Aligned Responses is sufficient for what we need.
The crosstabs from the Related tab look different from the crosstabs created by other tabs in the Categorical platform. Instead of having separate tables for each response column, they are all placed into one. There is a row for each response, and each value is given a column. The values are common across all the responses, because the platform expects Aligned Responses to work this way.
A centered Likert share chart appears below the crosstab and has the same layout. There is a bar for each row in the table. For each row, the mean is considered the "center" of the response, and the bar is shifted left or right, depending on whether there are more responses at the higher levels or the lower levels. The colors for the values across the top of the table match the colors in each section of the bar. You can easily see that more people agree with “I am the kind of person who knows what I want to accomplish in life and how to achieve it (ACOMPLSH)” than with any of the other statements. Most people are not confident about their ability to perform better than average in a fist fight (FISTFGT). The bar for CHANCES is shifted to the right, and the bright red bar is wider than the others, showing that more people “Definitely Agree” that they don’t like to take chances than they “Definitely Agree” with the other statements.
Refining the analysis
It’s often important to see how different categories of people responded to different questions, i.e., if there is a predictor variable that can be used as a proxy for other variables. Let’s change the report slightly. Instead of looking at everything as a response, let’s use one of the questions, “I have better taste than most people” (BETTASTE) as a proxy for a person’s self-esteem. Instead of assigning it as part of the Aligned Responses, we’ll make it an X Column.
Now when we click OK, we get a series of crosstabs: One for each of the questions designated as a response, with a row for each value of BETTASTE within each table. The tables are stacked on top of each other, creating a long crosstab that can be difficult to read. Sometimes, I turn it off using the option from the Categorical platform’s red triangle menu.
The Share chart clearly shows what might be difficult to see in the numbers: Each question has its own mean measuring how much, on average, respondents agreed with the statement, but if we examine each of the questions based on how much respondents agreed with “I have better taste than most people”, we see that the bars shift to the right as you move down the row within each sub-table.
People who responded “Definitely Agree” to the BETTASTE question were more likely to “Definitely Agree” that “I am the kind of person who knows what I want to accomplish in life and how to achieve it” and they were more likely to “Definitely Agree” with “I would do better than average in a fist fight”.
The only question in this group that appears to be unrelated to BETTASTE is the statement “I don’t like to take Chances,” since the bars in that table do not shift with the answer for BETTASTE.
Give it a try!
Aligned Responses is a convenient way to explore surveys that have many questions with the same ordinal coding (such as “Strongly agree” – “Strongly Disagree” or “Poor” to “Excellent” ratings on a product or service). The Share chart, in particular, is a quick and easy visual that can help you spot patterns in your data that might be hidden in a large table of counts and percentages.
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