ncases: Number of Cases in Data
In quest: Prepare Questionnaire Data for Analysis

Description Usage Arguments Value See Also Examples

ncases counts how many cases in a data.frame there are that have a specified frequency of observed values across a set of columns. This function is similar to nrow and is essentially partial.cases + sum. The user can have ncases return the number of complete cases by calling ov.min = 1, prop = TRUE, and inclusive = TRUE (the default).

1	ncases(data, vrb.nm = names(data), ov.min = 1, prop = TRUE, inclusive = TRUE)

`data`	data.frame or matrix of data.
`vrb.nm`	a character vector of colnames from `data` specifying the variables.
`ov.min`	minimum frequency of observed values required per row. If `prop` = TRUE, then this is a decimal between 0 and 1. If `prop` = FALSE, then this is a integer between 0 and `length(vrb.nm)`.
`prop`	logical vector of length 1 specifying whether `ov.min` should refer to the proportion of observed values (TRUE) or the count of observed values (FALSE).
`inclusive`	logical vector of length 1 specifying whether the case should be included if the frequency of observed values in a row is exactly equal to `ov.min`.

integer vector of length 1 providing the nrow in data with the given amount of observed values.

partial.cases nrow

vrb_nm <- c("Ozone","Solar.R","Wind")
nrow(airquality[vrb_nm]) # number of cases regardless of missing data
sum(complete.cases(airquality[vrb_nm])) # number of complete cases
ncases(data = airquality, vrb.nm = c("Ozone","Solar.R","Wind"),
   ov.min = 2/3) # number of rows with at least 2 of the 3 variables observed