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We model disease-marker association in a candidate region via a hidden Markov process and allow for correlation between linked marker loci.
Multilevel models were fitted to allow for correlation between repeated measures.
These models allow for correlation between repeated measurements and for both fixed and random effects.
That is, we allow for correlation between random parameters in the model.
To allow for correlation between observations on the same pairs in separate waves, robust (Huber–White) estimates of standard errors were used.
To allow for correlation between EDE measures within the same therapy group, a further random effect will be included that varies with therapy arm.
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We used robust variance estimation to allow for correlations between pregnancy outcomes in each woman.
A random effect of patient was specified to allow for correlations between repeated measures within participants.
To allow for correlations between the factors, a promax oblique rotation was used to simplify the factor structure [ 39- 41].
To allow for correlations between members of the same family, Huber and White robust estimators of variance were used, considering women clustered within families (Huber, 1967).
Because of the categorical nature of several variables in our analysis, we did not allow for correlations between variables and did not specify associations between sex, alcohol, smoking, and physical activity, for instance.
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CEO of Professional Science Editing for Scientists @ prosciediting.com