# validComputations

##### Only compute means or sums for cases with enough nonmissings

These functions have been written as equivalents of SPSS' `MEAN.x`

and `SUM.x`

functions, which only compute means and sums if enough cases have valid values.

- Keywords
- manip

##### Usage

```
validMeans(...,
requiredValidValues = 0,
returnIfInvalid = NA,
silent = FALSE)
validSums(...,
requiredValidValues = 0,
returnIfInvalid = NA,
silent = FALSE)
```

##### Arguments

- ...
Either a dataframe or vectors for which to compute the mean or sum.

- requiredValidValues
How many values must be valid (i.e. nonmissing) to compute the mean or sum. If a number lower than 1 is provided, it is interpreted as proportion, and the number of variables is computed. For example, if

`requiredValidValues=.8`

, 80% of the variables must have valid values. If 'all' is specified, all values must be valid (in which case the functions are equal to`rowMeans`

and`rowSums`

).- returnIfInvalid
Wat to return for cases that don't have enough valid values.

- silent
Whether to show the number of cases that have to be valid if

`requiredValidValues`

is a proportion.

##### Value

A numeric vector with the resulting means or sums.

##### See Also

##### Examples

```
# NOT RUN {
validMeans(mtcars$cyl, mtcars$disp);
validSums(mtcars$cyl, mtcars$disp, requiredValidValues = .8);
### Or specifying a dataframe
validSums(mtcars);
# }
```

*Documentation reproduced from package userfriendlyscience, version 0.7.2, License: GPL (>= 3)*