Convert mfrm_fit to a tidy data.frame

Returns all facet-level estimates (person and others) in a single tidy data.frame. Useful for quick interactive export: write.csv(as.data.frame(fit), "results.csv").

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 added in 0.1.6 ("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_core")
fit <- fit_mfrm(toy, "Person", c("Rater", "Criterion"), "Score",
                method = "JML", model = "RSM", maxit = 30)
head(as.data.frame(fit))
#>       Facet Level   Estimate Extreme
#> P001 Person  P001  0.6857247    none
#> P002 Person  P002  1.6727706    none
#> P003 Person  P003  1.2575190    none
#> P004 Person  P004  0.9010429    none
#> P005 Person  P005  0.9010429    none
#> P006 Person  P006 -1.5244704    none