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Formal comparisons between groups of differences in the prevalence of symptoms, using logistic regression models, are shown in Fig. 2.
The discriminate validity evidence is that the scale can distinguish between groups of differences, the evidences are as follows: First, the result showed that the group with poorer self-report stroke knowledge before testing had a higher SPDBI score than the group with better knowledge.
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No significant differences between groups of different severity were found, but regional differences existed.
We showed the imbalance between groups of patients using differences of proportions as all variables were categorical (appendix 1).
Differences between groups of continuous variables are shown as differences in means with 95% confidence intervals (95% CI).
However, modelling allows greater understanding of differences between groups of interest.
Statistical significance of differences between groups of data was assessed with the Student's t test.
Statistical significance of differences between groups of patients is based on Mann-Whitney U.test.
Further study is needed to extend the analysis of differences between groups of patients on the clinical aspects.
The statistical significance of differences between groups of patients in continuous parameters was tested using the Mann-Whitney U test.
The between-group analyses of difference scores (TETRA – sham) revealed a significant difference for both total symptom score and total number of symptoms reported (Table 5).
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CEO of Professional Science Editing for Scientists @ prosciediting.com