Descriptive summaries for a partial ordering/ranking dataset
Compute rank summaries and censoring patterns for a partial ordering/ranking dataset.
rank_summaries(data, format_input, mean_rank = TRUE, marginals = TRUE, pc = TRUE)
data |
Numeric NxK data matrix of partial sequences. |
format_input |
Character string indicating the format of the |
mean_rank |
Logical: whether the mean rank vector has to be computed. Default is |
marginals |
Logical: whether the marginal rank distributions have to be computed. Default is |
pc |
Logical: whether the paired comparison matrix has to be computed. Default is |
A list of named objects:
|
Numeric vector of length N with the number of items ranked by each sample unit. |
|
Frequency distribution of the |
|
Numeric 3xK matrix with the counts of sample units that ranked or not each item. The last row contains the total by column, corresponding to the sample size N. |
|
Numeric vector of length K with the mean rank of each item. |
|
Numeric KxK matrix of the marginal rank distributions: the (i,j)-th entry indicates the number of units that ranked item i in the j-th position. |
|
Numeric KxK paired comparison matrix: the (i,i')-th entry indicates the number of sample units that preferred item i to item i'. |
Cristina Mollica and Luca Tardella
Marden, J. I. (1995). Analyzing and modeling rank data. Monographs on Statistics and Applied Probability (64). Chapman & Hall, ISSN: 0-412-99521-2. London.
data(d_carconf) rank_summaries(data=d_carconf, format_input="ordering")
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