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Generalised Linear Mixed Modelling was used in order to take into account the repeated measures study design.
General Linear Mixed Modelling was used to test for relationships between initial face colour and colour change applied to optimise healthy appearance (dependent variable = colour change; random factor = participant ID; covariates = initial face colour: L*, a* and b*).
In the cross-cultural study, General Linear Mixed Modelling was used to test for effects of face ethnicity, participant ethnicity and the interaction between the two on colour change applied (dependent variable = redness change applied; fixed factor = face ethnicity; random factors = participant ethnicity, participant ID; covariates = initial face colour: L*, a* and b*).
Non-linear mixed modelling was employed for the analysis of the OKZ PK data.
The linear mixed modelling was carried out using STATA version 11.
Generalized linear mixed modelling was used, of HH compliance per observation session.
Similar(52)
Survival analyses and mixed modelling is then used to compare the treatment and control group.
A mixed model was used to evaluate the predictor variables.
To analyze data from human plasma, a linear mixed model was used.
Mixed model was used to assess relation between lipidomics variables and sum of EPA and DHA.
A P-value <0,05 (linear mixed model) was considered significant.
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