42 research outputs found
A factor analysis of the SSQ (Speech, Spatial, and Qualities of Hearing Scale)
OBJECTIVE:
The speech, spatial, and qualities of hearing questionnaire (SSQ) is a self-report test of auditory disability. The 49 items ask how well a listener would do in many complex listening situations illustrative of real life. The scores on the items are often combined into the three main sections or into 10 pragmatic subscales. We report here a factor analysis of the SSQ that we conducted to further investigate its statistical properties and to determine its structure.
DESIGN:
Statistical factor analysis of questionnaire data, using parallel analysis to determine the number of factors to retain, oblique rotation of factors, and a bootstrap method to estimate the confidence intervals.
STUDY SAMPLE:
1220 people who have attended MRC IHR over the last decade.
RESULTS:
We found three clear factors, essentially corresponding to the three main sections of the SSQ. They are termed "speech understanding", "spatial perception", and "clarity, separation, and identification". Thirty-five of the SSQ questions were included in the three factors. There was partial evidence for a fourth factor, "effort and concentration", representing two more questions.
CONCLUSIONS:
These results aid in the interpretation and application of the SSQ and indicate potential methods for generating average scores
Newton Algorithms for Analytic Rotation: an Implicit Function Approach
component loss criterion, factor analysis, gradient projection algorithm, oblique rotation, orthogonal rotation, orthogonal matrix, planar algorithm, principal components,
A simple general method for oblique rotation
factor analysis, gradient projection, quartimin, oblimin, target rotation, simplimax, similarity and simplicity, stationary points,
Rotation to simple loadings using component loss functions: The orthogonal case
Factor analysis, component loss criteria, gradient projection, hyperplane count methods, quartimax, minimum entropy, simplimax, sorted absolute loading plots, varimax,
Concise formulas for the standard errors of component loading estimates
asymptotic standard errors, principal component analysis, component loadings, rotation, information matrix, least squares,
A direct derivation of the REML likelihood function
REML likelihood, mixed models,