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Data triangulation and mixed methods analysis will also be used where possible.
Mixed methods analysis will involve the use of qualitative data to lend insight to quantitative findings.
This type of mixed methods analysis will serve as methods triangulation (checking the consistency of findings generated by different methods) [ 24, 33].
At the end of the study, mixed methods analysis will involve comparing results to increase understanding, specifically the use of qualitative data to lend insight to quantitative findings.
34 Once data collection is complete across all objectives, mixed methods analysis will be conducted to provide a holistic meta-analysis.
This mixed methods analysis will provide a much deeper understanding of patient reporting of safety in care transfers than would have been possible if analysing the components in isolation.
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Integrated mixed-methods analysis will be challenging as agreement will be difficult if researchers in a team come from different traditions (Small, 2011, pp. 77 79).
Methods for analysis will be as previously described [ 35].
Factor analysis and item response theory methods (Rasch analysis) will be used to further test scale unidimensionality.
Further, all outcome data will be screened for normality and, if necessary, logarithmic transformations or non-parametric methods of analysis will be applied.
If the efficacy and clinical outcomes are similar with both methods, the analysis will be limited to a comparison of costs, in order to identify the least expensive treatments.
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