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The average percentage of respondents answering all items of a factor was 94% therefore any resulting biases should be small.
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Finally, item-rest correlations between individual items and the sum of the remaining items on a factor were calculated.
Higher loadings of each item on a factor are indicated in bold text.
The loading of an item on a factor within a model was estimated using the maximum likelihood method.
Higher loadings of each item on a factor and higher correlations with a SF-12 component are indicated in bold P < 0.01 for all correlations The PCS-12 and MCS-12 summary scores explained 93.2% and 86.9% of the total variance of the PCS-36 and MCS-36 summary scores respectively (expected standard 90%), supporting content validity of the Greek SF-12.
Basically, four criteria were used for excluding items, namely: (a) Item impairs or has a negative impact on factor's internal consistency, (b) item presents too little of an interpretative consistency to be kept for the factor, (c) significant loadings in more than one factor (difference lower than 0.50 in intrafactor loadings), and (d) content redundancy among items of a same factor.
30 The contribution of each item to a factor is expressed in factor loadings.
A factor pattern matrix was generated, which contained the loadings that represented the unique relationship of each item to a factor, after controlling for the correlation among the factors [ 47].
Cronbach's alpha was used to test internal reliability of Likert types of items and a factor loading of 0.3 or greater was the criterion used to retain items.
Factor I Eye Irritation 17.2% Factor II Convenience of Use 16.1% Factor III Ease of Use 15.3%Factor IV Hyperemia 15.2% Factor V Effectiveness 8.1% Individual scores were computed by equating the scale range of items, adding the scale values of items within a factor, and transforming the resulting value into a score between 0 and 100.
Observations with missing values for > 50% of items within a factor were excluded from the analysis.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com