consensus_df: Consensus for data frame
In kthorstmann/consr: Compute Consensus For Likert Scales

Description Usage Arguments Details Value Examples

Compute the consensus for all items of a data frame, based on Tastle & Wiermann, (2006).

1 2	consensus_df(data, range = NULL, consensus.only = FALSE, round = 2, check.int = TRUE)

`range`	The range of the items indicating the valid values. Default is `NULL`.
`consensus.only`	Logical, if only the consensus should be reported. Default is to `FALSE`.
`round`	The number of digits to round the result to. Default is to 2.
`check.int`	Whether the function should check for integers. Default is to `TRUE`. Only integers are allowd. If `FALSE`, things can go horribly wrong.
`item`	The dataframe with the items, for which the conensus should be computed.

n: The number of valid answers on that item
min: The minimum answer on that item
max: The maximum answer on that item
consensus: The consensus
dissensus: The dissensus
n_missing: The absolute number of missing values on that item, defined as NA
perc_missing: The relative number of missing values on that item, defined as NA

Returns an data frame with the consensus and additional information for each item. See details for further explanation.

n = 10 # (max = 26 for now)
var_names <- paste0("var_", letters[1:10])
entries <- matrix(sample(-2:2, n*10, replace = TRUE),
                 nrow = n, ncol = 10)
entries[sample(1:100, 15)] <- NA
data <- as.data.frame(entries)
colnames(data) <- var_names
subj_id <- paste0("id_", sample(letters, n, replace = FALSE))
data <- cbind(subj_id, data, stringsAsFactors = FALSE)
data["var_j"] <- data["var_j"] / 2.3
consensus_df(data, range = c(-2, 2), check.int = TRUE)