summary and VarCorr¶

Human-readable summaries and variance-covariance tables for fitted mixed models.

summary()¶

result.summary() returns a SummaryResult that renders an lme4-style text summary matching summary.merMod() in R. The output includes scaled residuals, random-effects variance table, fixed-effects coefficients with Satterthwaite DFs and p-values, and convergence status.

import interlace

result = interlace.fit("score ~ hours + gpa", data=df, groups=["student", "school"])
print(result.summary())

statsmodels compatibility¶

SummaryResult has a .tables property returning [info_df, fe_df]:

tables[0] — model info (method, nobs, log-likelihood, AIC, BIC)
tables[1] — fixed-effects table with columns Coef., Std.Err., z, P>|z|, [0.025, 0.975] — matching statsmodels.MixedLMResults.summary()

s = result.summary()
fe_table = s.tables[1]  # DataFrame, compatible with statsmodels consumers

VarCorr()¶

VarCorr(result)[source]¶

Return variance-covariance components from a fitted model.

Parameters:: result – A CrossedLMEResult from fit().
Return type:: VarCorrResult
Returns:: VarCorrResult – Object with an as_dataframe() method returning columns grp, var1, var2, vcov, sdcor — matching as.data.frame(VarCorr(fit)) in R.
Parameters:: result (CrossedLMEResult)

Examples

>>> vc = interlace.VarCorr(result)
>>> vc.as_dataframe()

Returns variance-covariance components in the same format as R’s as.data.frame(VarCorr(fit)).

Example¶

from interlace import VarCorr

vc = VarCorr(result)
print(vc.as_dataframe())
#         grp           var1  var2    vcov    sdcor
# 0  school_id  (Intercept)  None   0.412    0.642
# 1   Residual         None  None   1.284    1.133

Columns¶

Column	Description
`grp`	Grouping factor name, or `"Residual"`
`var1`	Random-effect term name (e.g. `"(Intercept)"`)
`var2`	Second term for correlations; NaN for variances
`vcov`	Variance or covariance value
`sdcor`	Standard deviation (diagonal) or correlation (off-diagonal)

For random-slope models, off-diagonal entries show the correlation between the intercept and slope random effects.

VarCorrResult¶

class VarCorrResult(result)[source]¶

Structured variance-covariance components from a fitted mixed model.

Mirrors the output of R’s VarCorr() function.

Parameters:: result (CrossedLMEResult)

as_dataframe()[source]¶

Return variance components as a DataFrame.

Columns: grp, var1, var2, vcov, sdcor

Matches the output of as.data.frame(VarCorr(fit)) in R.

Return type:: Any