analyze: Generate basic psychometrics from data and key
In zief0002/QME: Classic test theory item analysis

Returns object with basic psychometrics of a test from data and key

1 2	analyze(test, key = NULL, create_key = FALSE, id = TRUE, d = 2, use = "pairwise.complete.obs", na_to_0 = TRUE)

`test`	A `data.frame` containing subjects as rows and items as columns. If `id = TRUE`, the first column should be an id column.
`key`	Provides information on how to score the test. If `NULL`, the default, then test is assumed to be already scored. Two formats are accepted for the key. A simple key can be provided as a named vector or single-row data frame, where the names are the names of the items and the values are the correct answer (scored 1, and all other responses scored 0). If the scoring scheme is more complex, a full key can be provided; this must be provided as a `data.frame` where the first column, `response`, contains all the possible responses to any item, and the subsequent columns correspond to each item with each value in that column representing that item's score for that row's response. See `vignette("scoring")` for more help on setting up the key.
`create_key`	For SCORED data only, creates a dummy key mapping input to output values. This allows the distractor analysis to be used for scored data
`id`	Is there an id column provided for the test? If `FALSE` an id column is automatically created and added.
`d`	Number of digits for summary outputs
`use`	Which observations to use (e.g. with or without missing values) for calculating difficulty and covariance-based measures? See `use` argument in `cov`
`na_to_0`	When scoring, assume that NAs are scored as 0? Default is TRUE