Convert mfrm_fit to a tidy data.frame

Returns all facet-level estimates (person and others) in a single tidy data.frame. Person rows retain their original identifiers; review or transform them before writing the result outside a controlled analysis environment.

Usage

# S3 method for class 'mfrm_fit'
as.data.frame(x, row.names = NULL, optional = FALSE, ...)

Arguments

x

An mfrm_fit object from fit_mfrm.

row.names

Ignored (included for S3 generic compatibility).

optional

Ignored (included for S3 generic compatibility).

...

Additional arguments (ignored).

Value

A data.frame with columns Facet, Level, Estimate, and Extreme. The Extreme column is populated for person rows from the extreme-score flag ("Min" / "Max" / NA); non-person facet rows carry NA in that column by design.

Details

This method returns four columns (Facet, Level, Estimate, Extreme) so that the result is easy to inspect, join, or write to disk.

Interpreting output

Person estimates are returned with Facet = "Person". All non-person facets are stacked underneath in the same schema.

Typical workflow

1. Fit a model with fit_mfrm().

2. Convert with as.data.frame(fit) for a compact long-format export.

3. Join additional diagnostics later if you need SE or fit statistics.

See also

fit_mfrm, export_mfrm

Examples

toy <- load_mfrmr_data("example_operational")
fit <- fit_mfrm(toy, "Person", c("Rater", "Criterion"), "Score",
                method = "MML", model = "RSM",
                quad_points = 7, maxit = 30)
head(as.data.frame(fit))
#>    Facet Level    Estimate Extreme
#> 1 Person  P001  0.22371868    none
#> 2 Person  P002  0.71054603    none
#> 3 Person  P003  0.02517584    none
#> 4 Person  P004  0.14530707    none
#> 5 Person  P005 -0.06792434    none
#> 6 Person  P006  0.70720576    none