Description Usage Arguments Details Value References Examples
Calculate best-worst scores for each respondent-item combination. This is simply taking the total number of times a respondent selected the item as "best" and subtracting from that the number of times a respondent selected the item as "worst" (Louviere et al., 2013).
1 | diffscoring(data, id, block, item, choice, std = FALSE, wide = FALSE)
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data |
A data.frame of the type described in details. |
id |
A string of the name of the id column. |
block |
A string of the name of the block column. |
item |
A string of the name of the item column. |
choice |
A string of the name of the choice column. |
std |
Logical of whether or not one wants to standardize the data to a -1 to +1 range. |
wide |
Logical of whether or not one wants the data returned in long (each row is an item-respondent combination and all best-worst scores are in the same column) format (FALSE) or in wide format (where each row is a respondent, and the best-worst scores for the items are in their own columns). See the 'indiv' data as an example. |
This function requires data to be in a specified format. Each row must represent a respondent-block-label combination. That is, it indicates the person, the block (or trial), the item that was judged, and a column indicating whether it was chosen as best (+1), worst (-1), or wasn't selected as either (0).
A data.frame containing the id and item columns as well as a "bws" column that indicates the best worst score. If 'wide = TRUE', then each item has its own column and the bws is filled-in those columns.
Louviere, J., Lings, I., Islam, T., Gudergan, S., & Flynn (2013). An introduction to the application of (case 1) best-worst scaling in marketing research. International Journal of Research in Marketing, 30(3), 292-303. doi: 10.1016/j.ijresmar.2012.10.002
1 2 3 4 | data(indiv)
head(indiv)
diffscoring(indiv, "id", "block", "label", "value")
diffscoring(indiv, "id", "block", "label", "value", TRUE, TRUE)
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