Comments (4)
Thanks, it may also affect the calculate_kmo
function.
from factor_analyzer.
Ah, you're right. Thanks for submitting the issue, I'll update this soon!
from factor_analyzer.
This is a good question.
We only use the cov()
function in CFA, which is still very much a work-in-progress. In general, want our output to imitate R's lavaan
package, and by default lavaan
is rescaling the sample covariance to the population.
However, you're right that if anyone wants to use this function outside of factor_analyzer
, this probably isn't what they want. I'll make ddof
an optional parameter. Let me know if you have other suggestions/concerns, or if I can close this issue.
from factor_analyzer.
Addressed this in the master
branch.
from factor_analyzer.
Related Issues (20)
- calculate_bartlett_sphericity() crashes with dataframe but not with numpy array HOT 1
- calculate_kmo() differs from psych.KMO() in R HOT 1
- FactorAnalyzer(method="principal") throws sklearn FutureWarning in randomized_svd() HOT 1
- how to get Proportion Explained, RMSR and chi-squared? HOT 1
- Current release on conda HOT 1
- Mistake in correlation-function HOT 2
- Only 3 factors appear in factor loading matrix, but "n_factors=5" as input. Likely my error but I cannot find it. HOT 1
- Add pre-commit checks and apply them to all existing code
- random initial values for rotation matrix in GPA rotations HOT 2
- Regression method to calculate factor scores HOT 1
- Optimization error
- Comparison with SPSS HOT 2
- Switch to using `nose2` for tests instead of `nose` HOT 1
- Add support for Python 3.11 HOT 1
- Remove pre-commit from install dependencies, add it to "dev" extra HOT 1
- get_factor_variance() returns ndarray which is not ordered by variance.
- SciPy sum function is deprecated causing Factor-Analyzer to fail HOT 4
- Loadings matrix has incorrect shape when using principal method with lapack HOT 1
- `UnboundLocalError` with principal-lapack method types and any oblique rotations HOT 1
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from factor_analyzer.