# rowNA: Frequency of Missing Values by Row In quest: Prepare Questionnaire Data for Analysis

## Description

`rowNA` compute the frequency of missing values in a matrix by row. This function essentially does `apply(X = x, MARGIN = 1, FUN = vecNA)`. It is also used by other functions in the quest package related to missing values (e.g., `rowMeans_if`).

## Usage

 `1` ```rowNA(x, prop = FALSE, ov = FALSE) ```

## Arguments

 `x` matrix with any typeof. If not a matrix, it will be coerced to a matrix via `as.matrix`. The argument `rownames.force` is set to TRUE to allow for rownames to carry over for non-matrix objects (e.g., data.frames). `prop` logical vector of length 1 specifying whether the frequency of missing values should be returned as a proportion (TRUE) or a count (FALSE). `ov` logical vector of length 1 specifying whether the frequency of observed values (TRUE) should be returned rather than the frequency of missing values (FALSE).

## Value

numeric vector of length = `nrow(x)`, and names = `rownames(x)`, providing the frequency of missing values (or observed values if `ov` = TRUE) per row. If `prop` = TRUE, the values will range from 0 to 1. If `prop` = FALSE, the values will range from 1 to `ncol(x)`.

`is.na` `vecNA` `colNA` `rowsNA`
 ```1 2 3 4 5``` ```rowNA(as.matrix(airquality)) # count of missing values rowNA(as.data.frame(airquality)) # with rownames rowNA(as.matrix(airquality), prop = TRUE) # proportion of missing values rowNA(as.matrix(airquality), ov = TRUE) # count of observed values rowNA(as.data.frame(airquality), prop = TRUE, ov = TRUE) # proportion of observed values ```