Your English writing platform
Discover LudwigExact(3)
The items variance showed that items varied in difficulty to some extent.
Communality values that demonstrated how well items' variance was explained by the five-factor solution ranged from 0.35 to 0.80.
To decrease confounding bias, we performed multivariate analyses: multiple regressions were carried out using a stepwise backward method, after ensuring sample adequacy, linearity of the model, residual normality and non-collinearity of retained items (variance inflation factor <2).
Similar(57)
Four tests were conducted: 1. Equal item variance: Items measuring the same concept should have roughly equal standard deviations and should be around 1.0 (for 5-choice response scales) [ 13]. 2. Equality of item-scale correlations: Items in each scale should contain approximately the same proportion of information about the concept being measured.
This second order construct, constituted by 15 items with an average CVR of.39, explained 62%% of variability of the 3 first order engagement dimensions with strong reliability (CR = .83) and good overall goodness-of-fit to the items' variance-covariance data (χ2/df = 2.78; CFI = .978; TLI = .974; RMSEA = .054).054
Seventeen and 15% of the item variance indicated that items differed in difficulty to a large extent.
Factor 1 (which accounted for 29% of item variance) was defined by six of the scale items.
Five statements were removed from the current analyses because of very low item variance for these items that was accounted for by their corresponding constructs.
The third Factor was defined by five of the scale items, accounted for 8% of item variance, and was labeled value of mathematics.
The third Factor was defined by five of the scale items, accounted for 7% of item variance, and was labeled performance orientation.
Factor 2 (which accounted for an additional 9% of item variance) was defined by eight of the scale items and was labeled self-efficacy.
More suggestions(3)
Write better and faster with AI suggestions while staying true to your unique style.
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