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Differences between subgroups will be tested formally [ 40- 42].

With subgroup analyses, potential variation between study results between subgroups will be analyzed.

Differences between subgroups will be explored using tests for subgroup differences expressed as p values.

Therefore, changes over time and differences between subgroups will be tested by using the Random Intercept Model.

Differences between subgroups will be determined using χ2 tests for categorical data and independent samples t-tests or ANOVAs for continuous variables.

The analysis of the association between the qualitative variables will be carried out using the chi-square test or Fisher's exact test and comparing the means of different quantitative variables between subgroups will be performed using t-test or ANOVA, or their nonparametric equivalent (Mann-Whiney or Kruskal-Wallis).

Similar(54)

Furthermore, if it is possible to subgroup patients into cam/pincer/mixed, valuable information about the differences between these subgroups will be obtained from this study.

Any differences between treatment effects within subgroups will be assessed by examining the significance of the subgroup by intervention interaction term within the model.

Furthermore, in the subsequent subgroup analysis, the estimated differences between treatment and control arms (and between the selected g+ and g− subgroups) will be attenuated and the conclusion could be incorrect.

Subgroups will be compared at baseline.

Furthermore, scenario analyses for relevant subgroups will be performed.

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