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Minimisation Minimisation ensures balance between intervention groups for several selected patient factors (such as age).
Minimization will be used to ensure balance between intervention groups for several patient factors.
Further, minimization will be used to ensure prognostic balance between intervention groups for relevant patient factors.
To protect against prognostic imbalance between groups, we are using minimisation to ensure balance between intervention groups for several patient factors.
Randomization was performed in variable blocks of 4 8, to ensure that both balance between intervention groups and blinding are maintained.
We are using minimisation to ensure balance between intervention groups for the following factors: age, prefracture living, prefracture functional status, American Society for Anesthesiologists (ASA) Class and centre number.
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5 We used stratification on the basis of age (≥50 or <50) to balance between the intervention groups the number of younger patients with normal bone quality sustaining high energy fractures and older patients with low energy (fragility) fractures related to osteoporosis.
** Difference was calculated between intervention group and control group.
We anticipate that the sample sizes will be approximately balanced between the intervention groups, but if unequal sample sizes occur for some reason, generalized least squares techniques will be used for the statistical analysis.
A simple spreadsheet calculator [ 59] embeds the empirical competitive hyperbolic relationship [ 60] to help clinicians design dietary interventions that can create sufficient differences in HUFA balance between intervention and control groups.
Other covariates were generally balanced between treatment groups.
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