A natural one - particularly when assuming linearly homogeneous utility functions - is to find alternative allocations that maximize the utility levels with a common multiplicative factor, subject to the balances.
NF-κB is a classical example of a transcription factor subject to negative feedback loops.
A two-factorial ANOVA yielded highly significant effects of both the factors experimental condition (baseline vs. storage, P = 0.0038; F = 20.9) and the random effects factor subject (P = 0.0025; F = 14.3).
The factor, subject, was considered as a random factor.
The data were then stratified by journal impact factor, subject category, domestic institution and collaborating country.
One such factor, subject to much speculation in recent years, is anaesthetics and/or anaesthetic technique.
The factor "subject" was assessed using linear mixed-effects model analysis performed on all activities, including a total of 430 data sets across all 10 subjects.
The volumetric data were then analyzed for interindividual and interhemispheric differences using a repeated measurement analysis of variance (ANOVA) with the following design: between-subject factor: gender; within-subject factors: area and side; blocking factor: subject.
For each query gene, there is x proportion of chance that the bit scores of all its hits are divided by a factor subject to a gamma distribution same as above.
Choice is a binary variable, coded 1 for wheel1 and 0 for wheel2; group is a fixed-effect factor; subject is a random-effect factor; e, v, and r are continuous fixed-effect predictors.
When these relationships were examined using a general linear model with meal as a fixed factor, subject as a random factor, and the three plasma AAs as covariates, only plasma Ala was significant (P=0.001).
