Sentences with word «varimax»

Given the new sample in Study 4, maximum likelihood analyses with Varimax rotation forced 5 factors which accounted for 53 % of the sample variance.

To address the second research question in Study 3, an exploratory factor analyses with a maximum likelihood method with Varimax rotation indicated 5 factors that accounted for 47 % of the sample variance.

Principal component analysis (PCA) was chosen as extraction method using Varimax rotation.

Varimax Orthogonal Transformation was conducted to test the factor structure of the questionnaire.

Factorial structures similar to the ones shown in previous investigations following varimax rotation were expected, that is, four factors in GHQ - 28 and nine in SCL -90-R.

For instance, Austin (1983) using principal - components analysis with varimax rotation found three factors among American college students.

A factor analysis of all the items on the survey (using Varimax rotation) revealed the following:

We scored the variables as 0,1,2,..., a higher score indicating greater involvement (Table 2), and grouped them by exploratory factor analysis, using the «principal factors» method with varimax rotation [30].

EFA employed principal components analysis methods with varimax rotation.

For better interpretation of the motor test battery, an exploratory factor analysis (principal components analysis, varimax rotation) was performed in order to reduce dimensions [27].

A varimax rotatation revealed that there were three items in each factor, and examination of the items found a distinct difference in language between the two factors.

An exploratory factor analysis with principal component method and with Varimax rotation was conducted on the sample.

Exploratory factor analysis (EFA) using principal component extraction method with Varimax rotation, was conducted to determine the factor structure of the items of the instrument (items with factor loadings ≥ 40 were retained).

In addition, Mahon [23] used an orthogonal varimax rotation and the two - factor solution was finally explored.

Rotation method: varimax with Kaiser normalization.

[The six marital quality items were factor analyzed using principal components analysis with varimax (orthogonal) rotation.

Again, we used an orthogonal, Varimax rotation with a. 4 item to factor criteria to interpret item loadings.

In the current administration, the internal consistency of the scale was 0.90 and as indicated by a maximum likelihood exploratory factor analysis with Varimax rotation, seven factors accounted for 47 % of the sample variance.

These involved principal components analyses extracting factors with Eigenvalues greater than 1 and with varimax rotation.

An unrestricted Maximum likelihood factor analysis with Varimax rotation was conducted with the 26 items included (we omitted the benefit and hinder items).

To examine the factorial structure of the R - UCLA 20 items we performed an exploratory factor analysis (principal components) with varimax rotation.

A principle components analysis using a varimax rotation and no fixed number of factors showed that each of the seven facilitative courtship items contributed to a single factor with item loadings ranging between 0.71 and 0.88.

Factor and regression analyses may look weak with 46 participants but actually, since 46 participants rated their feelings and completed the survey eight times over an eight - week period, we ran Principal Component Analysis (with Varimax rotation) for 46 x 8 = 368 cases.

Initial examination of the items using principal component analysis with varimax rotation to maximize variance, revealed three factors having an eigenvalue greater than one.