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PLMIX (version 2.1.1)

make_complete: Completion of partial rankings/orderings

Description

Return complete rankings/orderings from partial sequences relying on a random generation of the missing positions/items.

Usage

make_complete(data, format_input, nranked = NULL, probitems = rep(1,
  ncol(data)))

Arguments

data

Numeric \(N\)\(\times\)\(K\) data matrix of partial sequences to be completed.

format_input

Character string indicating the format of the data input, namely "ordering" or "ranking".

nranked

Optional numeric vector of length \(N\) with the number of items ranked by each sample unit.

probitems

Numeric vector with the \(K\) item-specific probabilities to be employed for the random generation of the missing positions/items (see 'Details'). Default is equal probabilities.

Value

A list of two named objects:

completedata

Numeric \(N\)\(\times\)\(K\) data matrix of complete sequences with the same format of the input data.

nranked

Numeric vector of length \(N\) with the number of items ranked by each sample unit of the input data.

Details

The completion of the partial top rankings/orderings is performed according to the Plackett-Luce scheme, that is, with a sampling without replacement of the not-ranked items by using the positive values in the probitems argument as support parameters (normalization is not necessary).

Examples

Run this code
# NOT RUN {
## Completion based on the top item frequencies
data(d_dublinwest)
head(d_dublinwest)
top_item_freq <- rank_summaries(data=d_dublinwest, format_input="ordering", mean_rank=FALSE, 
                                pc=FALSE)$marginals["Rank_1",]

d_dublinwest_compl <- make_complete(data=d_dublinwest, format_input="ordering", 
                                    probitems=top_item_freq)
head(d_dublinwest_compl$completedata)

# }

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