The phrase "adjusted for between" is not correct and does not convey a clear meaning in written English.
It may be intended to express a comparison or adjustment made between two or more entities, but the phrasing is awkward and unclear.
Example: "The results were adjusted for between the two groups to ensure accuracy."
Alternatives: "adjusted for the differences between" or "corrected for variations among".
Percentiles based on bootstrap procedure with 5000 replicates. 1 Utility scores at follow-up measurements are adjusted for between group baseline difference using the multiple regression method.
Because we expected different demographics between the two groups (that is, demographics such as age, and co-morbidities such as cirrhosis), we also adjusted for between group characteristics when the P ≤ 0.25.
These models are an advancement over conventional linear regression approaches because they effectively handle the hierarchical nature of serial growth data to essentially predict individual curves whilst simultaneously estimating an average or mean curve that has been adjusted for between individual variation [ 22].
Using mean centered exposures, we adjusted for between-subject group and between-phase exposure effects.
† adjusted for between-household variation and between-cluster variation as appropriate and a priori for latrine access, time to water and district.
However, because of the inability to obtain variance statistics, a post hoc decision was made to estimate the required information size using the pooled mean difference and variance, adjusted for between-study heterogeneity, from the current study.
Model 3: within experiment effects only: For the case where the data is not adjusted for between-experiment batch effects, the reference sample is not used and so there are only two coefficients in the vector β g.
All models included time since transplant entered as a factor variable and adjusted for between-subjects covariates, including sex, age, graft type, and conditioning regimen, as well as time-varying covariates, including steroid use and disease status.
To focus estimates of associations at the subject level, we adjusted for between-community and between-phase exposure effects as proposed by Janes et al. (2008) by using exposures that were mean-centered across community and phase [see Supplemental Material, Regression Model, Mean Centering Method (doi 10.1289/ehp.0901407)].
We also included state as a categorical variable in all models in order to adjust for between-state differences in the rate of residential fire mortality (e.g., due to geographical differences in house construction and household heating).
Linear regression used random effects to adjust for between-patient variations.
