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Update docstring for fit measures#310

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alyst wants to merge 4 commits intoStructuralEquationModels:develfrom
alyst:doc_fit_measures
Open

Update docstring for fit measures#310
alyst wants to merge 4 commits intoStructuralEquationModels:develfrom
alyst:doc_fit_measures

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@alyst
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@alyst alyst commented Feb 19, 2026

Expand a bit the docstrings for the fit measures.

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codecov bot commented Feb 19, 2026

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 71.39%. Comparing base (1f8d2a9) to head (d12bf4d).
⚠️ Report is 30 commits behind head on devel.

Additional details and impacted files
@@            Coverage Diff             @@
##            devel     #310      +/-   ##
==========================================
- Coverage   71.83%   71.39%   -0.45%     
==========================================
  Files          51       51              
  Lines        2223     2283      +60     
==========================================
+ Hits         1597     1630      +33     
- Misses        626      653      +27     

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alyst and others added 2 commits February 20, 2026 11:02
Co-authored-by: Maximilian Ernst <34346372+Maximilian-Stefan-Ernst@users.noreply.github.com>
Comment on lines +7 to +11
The degrees of freedom for the SEM with *N* observed variables is the difference
between the number of parameters required to define the multivariate normal
distribution of observed variables (*½N(N+1)* for the *N×N* covariance matrix,
plus *N* for the means vector if present), and the number of model parameters
(`nparams(model)`](@ref nparams)).
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Suggested change
The degrees of freedom for the SEM with *N* observed variables is the difference
between the number of parameters required to define the multivariate normal
distribution of observed variables (*½N(N+1)* for the *N×N* covariance matrix,
plus *N* for the means vector if present), and the number of model parameters
(`nparams(model)`](@ref nparams)).
The degrees of freedom for the SEM with *N* observed variables is the difference
between the number of observed data points (*½N(N+1)* for the *N×N* covariance matrix,
plus *N* for the means vector if present), and the number of model parameters
(`nparams(model)`](@ref nparams)).

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That's very helpful, I added on emore comment, otherwise I'm happy to merge.

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