Factor Analysis Sample Clauses

Factor Analysis. To explore the different dimensions captured in each fatigue questionnaire and also assess their relationship with anxiety and depression, simple descriptive analyses were applied to the data, as well as ▇▇▇▇▇▇▇▇’▇ correlations. In this study, correlations of r≥0.6 are reported as strong correlations, r≥4 and <6 as moderate correlations and r<4 as weak correlations. Cronbach’s alpha was used to test the internal validity of the items in the fatigue questionnaires. Cronbach’s alpha is a coefficient of internal consistency which is commonly used as an estimate of the reliability of a psychometric test. Where validity is concerned with the extent to which an instrument measures what it is intended to measure. [Following this an exploratory factor analysis of the fatigue questionnaires was undertaken. A rotated factor matrix was performed with all the questions from each questionnaire as well as the fatigue VAS and the HADS scores. In order to identify the most appropriate questions and reduce down the number of items, all items which were not highly correlated were excluded (loading <0.6). To further reduce this both clinical interpretation and statistics were employed to exclude any very similar questions. The questions were the examined by the investigator and a second rheumatologist and using clinical judgement and after agreement between the two clinicians if two questions had almost identical wording or it was felt they were asking the same question then the question with the lowest loading was rejected and the question with the highest loading was retained. For example: I feel nervous and I feel tense were felt to be asking the same question. The loading into the factor analysis rotated factor analysis was 0.889 for I feel nervous and 0.672 for I feel tense; therefore, I feel tense was excluded from the final model. Consideration was also made to ensure that each dimension was represented.