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Our model in total explains 31% of the variance in followers' preference for authoritarian leadership, 10% variance in their preference for benevolent and moral leadership, and 9% in their preference for transformational leadership.
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As a result, the total explained variance is limited.
Among Anglo-Australians, the prediction models were relatively weak, explaining 0 9% of the total explained variance in physical activity.
Factorial analysis overall for DI and AS (total explained variance = 44.16%) detected two correlated factors (r = 0.34, p < 0.01).
According to the results, the total explained variance for the first four factors was 62.57%, over 60%.
If total explained share is smaller than 50%, then the correspondence analysis is not a suitable choice.
Prediction models for physical activity among Vietnamese-Australians were much stronger, explaining 11 32% of the total explained variance, with father's support variables contributing consistently to these models.
ALS data improved model fit for saskatoon and huckleberry abundance models, with total explained variance (r2) ranging from 37.6 to 59.4%.
The principal component loading matrix obtained using correlation matrix of eleven parameters reveals that first three components together account for 93.71 % of the total explained variance.
After screening out these parameters, the principal component loading matrix of eleven parameters indicates that first three components together account for 94.491 % of the total explained variance.
The total explained variance was 17.194%, the eigenvalue was 1.719, and the factor loading values for each question were over.80, confirming validity.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com