checks: Miscellaneous input validation
In elisr: Exploratory Likert Scaling

Description Usage Arguments Details Value

A set of test functions to ensure valid input and give helpful advice if it is not.

check_df() guarantees that x is an appropriate data frame for the analysis. That means: It verifies that x has less than two variables (a single item can't build a core), x has column names (used to pre-build scls in the overlapping process), if the column names are unique, and not of type NA. It throws an error if any of these requirements are not met. Additionally, it warns the user if the provided colnames are not unique or NA.

check_sclvals() tests whether x is a two element vector and throws an error if not. Integers are coerced to be of type double. Additionally, the function ensures that the first value is smaller than the second. Remember that checking for a two element vector implicitly secures that x is not NULL (because NULL is a logical constant of length '0').

compare_sclvals() makes sure that the sclvals set with overlap() are equal to those set with disjoint(). It throws an error if not.

check_mrit() guarantees that the input is a double vector of length one. Moreover, the function secures that the lower bound is unique and ranges between '0' and '1' (it throws an error if not). In addition, it warns a user pre-determining a fragment.

check_ovlp() safeguards that x is a character vector of length '1'. That means, it throws an error if not. Note that switch() within disjoint() and overlap() takes care of the input string itself. It throws an error when the given character doesn't match any available option.

check_msdf() guards against inputs that are not of type 'msdf'. It throws an error if not.

check_neg() verifies that the input is a logical constant of length 1 and not a missing value (this is necessary because objects of type NA are logical constants of length 1, too).

check_comp() examines the correlation matrix, cor(df). It complains (throws an error) if no correlation in cor(df) is greater than the specified mrit_min.

check_df(x)

check_sclvals(x)

compare_sclvals(x, x_attr)

check_mrit(x)

check_ovlp(x)

check_msdf(x)

check_neg(x)

check_comp(x, mrit_min, use)

`x`	some arbitrary input to be checked.
`x_attr`	a numeric vector of length 2 indicating the start- and endpoint of a scale.
`mrit_min`	a numeric constant of length 1 to specify the marginal corrected item-total correlation.
`use`	an optional string to specify how missing values enter the analysis. See `use` in `cor` for details.