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The linear fits between mutation numbers and age shown in Fig. 1 were obtained using a robust mixed model where the dependent variable is the number of mutations or a given mutational signature, the fixed effect is age, and the random effect is the individual.
The relationships of K1, K2 or RETT to lenght of intubation was analysed by linear mixed model where tube brand and size were factors with random effects.
The relationships of K1, K2 or RETT to length of intubation was analysed by linear mixed model where tube brand and size were factors with random effects.
Data were analyzed using a linear mixed model where results are adjusted for variation within individuals.
Therefore we developed a mixed model where we adopted value with higher coefficient of determination in each age group.
The null distribution of the log2-transformed probe set-specific expression is estimated by fitting a normal mixed model where the subject effect is random.
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In order to take into account potential cluster effects, we used mixed models, where well numbers and dates were included as random effects.
For each borehole, monthly GWLs are simulated using empirical mixed models where the fixed effects are based on applying an impulse response function to the local monthly precipitation.
We consider a general class of mixed models, where the individual parameter vector is composed of a linear function of the population parameter vector plus an individual random effects vector.
In the former case, data from individuals on the same nest cannot be considered independent, so we used mixed models where "nest" could be fitted as a random factor, to avoid pseudoreplication.
These analyses were tackled by applying random intercept repeated-measures mixed models where individual was entered as a random effect and the linear and second order polynomial terms of age as predictors together with sex.
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