Hi all. I've been struggling with something for a few days, so I thought it might be time to ask for the community's help. Note, this is a pretty long problem description since it leads step by step through 5 analysis scripts that are embedded in the attached data table. I haven't been able to figure out a more concise way to illustrate my analysis goal and the problems I'm having meeting it. If anyone has the time to look at this and find a solution, I'd be grateful. I've been stuck on it for a few days now.
The attached data table, called "LottSurveyDataForJMP" has results from an anonymous survey of forest management professionals. The RespondentID field is a unique ID for each participant where the time stamp is used instead of their name to preserve anonymity. The remaining 12 columns have the multiple response data type, since each questions allowed participants to select one or more check box responses. My survey software used semicolons for response delineation, so each column has either a single response (e.g., "forester) or a set of responses separated by semicolons (e.g., forester; forest planner; researcher).
The first 2 multiple response columns, "Affiliation" and "Role" describe the demographic make up of survey respondents. Note that many respondents had more than one affiliation and/or more than one role. The remaining 10 multiple response fields are answers to 10 different survey questions, numbered Q1 to Q10. My analysis goal is to summarize responses to each of these 10 questions by unique combinations of Affiliation and Role (e.g., State Agency * Forester or Non-profit organization * Forest Planner).
I have been able to figure out how to generate single factor summaries for all 10 questions by either Affiliation or Role using the categorical platform. The data table script called "All questions, 1 factor, "each individually" grouping" produces this result. However, I have not been able to figure out how to generate clean summaries of responses to each of the 10 questions by unique 2 factor interaction (e.g., Affiliation * Role). Instead, the first factor is parsed correctly, but the second factor is not. See my failed attempt to do this by running the data table scripts: "All questions, 2 factors, "combinations" grouping" or "All questions, 2 factors, "both" grouping." The only difference between these two scripts was in the value I selected for the "grouping type" drop down menu. Interestingly, selecting either "combinations" or "both" resulted in the same exact tables. In each of these cases, the same 2 factor table is created with Role levels nested within Affiliation levels, BUT... the role levels are no longer unique (e.g., State Agency affiliations are split out into 3 levels: "forester", "forest planner", and "forester; forest planner", when they should be split into only 2 unique levels: "forester" or "forest planner," where the case for the respondent who specified two roles as "forester; forest planner" should be assigned once to each of the separate categories, rather than retained as its own unique level.
Next, I used the "structured" tab of the categorical platform dialog to assign "role" to the "top" position and "affiliation" to the "side" position (run the "use of "structure" tab..." data table script to see this result. This produced exactly the type of two way table that was looking for, summarizing all unique 2 way combinations of Role and Affiliation. In this case, both demographic factors were treated the same way that the "each individually" grouping dealt with single x groping factors. This is exactly the table structure I am looking for in order to summarize results for each of the 10 survey questions. Unfortunately... when you run the next script "attempt to get unique role * affiliation results for individual questions..." you'll see that I wasn't able to generate the desired 2 factor summaries for individual questions.
I am hoping to create an output that looks exactly like the one I got for the "use of "structure" tab..." script where there are 10 tables, one for each question, with results summarized by unique combinations of role and affiliation, but I can't for the life of me figure out how to get this to work.