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However, none of these residuals has yet been extended to be applicable in the mixed regression context.
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We use the mixed regression method proposed by Newey and West (1987) to regress Eqs.
Data were analyzed with mixed regression.
Data were analyzed using a multivariable linear mixed regression model.
(24) and (25), in order to weaken heteroscedasticity and sequence dependency that mixed regression may cause.
For instance, a mixed regression model that incorporates random effects may be appropriate.
Due to the heterogeneity of the data, meta-analyses and mixed regression modeling were not conducted.
Mixed regression analyses confirmed outcome and process effects that were apparent through visual inspection.
Different linear mixed regression models (PROC MIXED, SAS 9.4, SAS Institute Inc).
Statistical analysis was performed with a linear mixed regression model.
Mixed regression models for repeated-measures were used.
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