Sentence examples for the responses were analysed using from inspiring English sources

The responses were analysed using IBM SPSS Statistics (Version 20).

The factor structure of the responses were analysed using AMOS, a program that performs confirmatory analysis (CFA).

The responses were analysed using the Binomial Probability test (Statistical Package for the Social Sciences [SPSS], Version 14) to analyse potential differences in preference for anti-TNF therapies, a p value of < 0.05 was considered statistically significant.

The responses were analysed using a nonparametric approach and confirmed our initial observations.

The questionnaire responses were analysed using the Statistical Package for Social Sciences (SPSS) for Windows version 19 and Microsoft Office Excel 2007.

Focus group data remained grouped under the six questions that were discussed during the session and responses were analysed using Summative Content Analysis.

The open-ended responses were analysed using inductive content analysis, with NVivo software (version 10.0).

The audio-files, transcripts and questionnaire responses were analysed using the six-step structured approach outlined by Smith, Flowers and Larkin [ 6].

Data dimensionality was investigated using the approach suggested by Linacre (1998) [ 38] and item responses were analysed using the Partial Credit Model [ 35], considering model fit, item and category locations, and differential item functioning (DIF) regarding sex, age group and etiology (i.e. MS or SCI).

Paired responses were analysed using the Wilcoxon Rank Sum Test for non-parametric data.

These responses were analysed using the same procedure as described above.