Sentence examples for adjustment were used from inspiring English sources
Mixed models with similar covariate adjustment were used to obtain adjusted regression estimates accounting for repeated measurements of blood pressure (using repeated statement in the modeling).
Two predefined models of adjustment were used (model 1: univariate; model 2: adjusted for sex, age, BMI, hypertension, smoking, glomerular filtration rate, triglycerides, LDL cholesterol, and HDL cholesterol).
Four predefined models of adjustment were used (model 1: unadjusted; model 2: adjusted for sex and age; model 3: adjusted for sex, age, BMI, hypertension, smoking, glomerular filtration rate, triglycerides, LDL cholesterol, HDL cholesterol, and FS; and model 4: model 3 with additional adjustment for fasting glucose).
Where appropriate, paired-sample t tests using the Bonferroni adjustment were used to indicate changes compared to Pre-Ex.
The parameters obtained from this adjustment were used as dependent variables for the formulation of the empirical equations of the factorial design tested.
Trigram language models were trained on both in-domain and out-of-domain datasets, where word-class mixture trigram language models with weights obtained from a procedure of forward weight adjustment were used [37].
A Bonferroni adjustment was used to adjust for multiplicity [ 26].
The step-down max T adjustment is used to calculate adjusted p values to account for the multiple hypotheses tested.
The direct method of age adjustment was used to calculate age-adjusted incidence and mortality rates.
To adjust for multiple testing errors, a step-up Benjamini false discovery rates (FDR) adjustment was used.
