Once you've collected 3CM data from the individuals in your study, you must convert the data into a form that can be understood by Anthropac. The file can be created in Notepad or another application that saves a .txt file type. The easiest way to create the data file is to work from an example. Download my sample data file using the button below, then we'll walk through it line-by-line. 

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Now let’s walk line-by-line through the contents of the file.

 

DL nm=12 n=57

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nm should equal the number of participants included in the data set.

n should equal the number of terms in the 3CM activity.

 

format = ps

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ps indicates the pilesort module of Anthropac. Don’t change this.

 

matrix labels:
p4, p10, p14, p23, p24, p27, p28, p30, p32, p43, p48, p49

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matrix labels are the names or numbers assigned to each participant in the data set. To maintain confidentiality, I prefer to use numbers. The number of matrix labels must equal nm from above.

 

labels:
Agricultural_Best_Management_Practices, Agricultural_Fertilizer, Agricultural_Regulations…

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labels are the terms used in the 3CM activity. The number of labels must equal n from above.

 

data:
# p4
44 47 1 19 7 28 41 10 18 54 46 56 6 32 26 2
21 16 4 30 52 43 20 36 38 3 35 57 45
13 25 5 22 15 31 27 42 17 39 24 53 50 29 40 55
48 34 12 8 23 37 33 11 51;
# p10
25 46 6 53 32 2 26
44 7 47 41 57 19 16 40 15
52 48 28 33 35 51
3 49 39 23 4 14 1 12 37;
…

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data contains 3CM results from each participant and the pound sign (#) indicates the starting point of each participant's data - in this data set, p4 is the first participant. Notice that p4 is also the first participant listed under matrix labels - the participant data entries must be the same as the matrix labels.

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The numbers following the participant ID indicate the terms and clusters in the participant’s 3CM results. Each number represents a specific 3CM term from the labels section above. The first term listed under labels, “Agricultural_Best_Management_Practices,” is assigned the number 1; the second term, “Agricultural_Fertilizer,” is assigned the number 2; and so on.

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Each row of numbers indicates terms that were clustered together by the participant. For example, participant p4 had a cluster containing terms 44 47 1 19 7 28 41 10 18 54 46 56 6 32 26 2, another cluster containing terms 21 16 4 30 52 43 20 36 38 3 35 57 45, as well as two additional clusters. A semicolon must be entered at the end of the participant’s final cluster.

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Step 4: Generate a Map of Associations Between Terms

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