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Using an interaction model in DEXSeq we identified genes which show differential exon usage due to the interaction of strain and colony (FDR < 0.01).
However, in data sets exhibiting complex co-variance patterns (such as W3), joint analysis of all environments using an interaction model imposes inadequate restrictions on co-variance patterns and, consequently, bivariate analysis seems more appropriate.
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As described by Peart et al. (2005), we used an interaction model to compare the response to SAHA versus the response to depsipeptide at the 16 h point.
This study explores agro-ecosystem modelling using an interaction graph-based modelling approach that explicitly link elements at different scales without up or downscaling.
Commonly used in longitudinal observational research, the linear growth curve technique enables the identification of changes over time by using an interaction term in the model to determine if those changes are significant.
An extended Cox model using an interaction term of time and zoster exposure was introduced to take into account the effect of drop out and follow-up time.
We assessed effect modification using an interaction term in the models while also including the main effects of season and pollution.
Experimental results were fitted with the Flory–Huggins model using an interaction parameter depending on both temperature and composition.
When systolic blood pressure was included in the model using an interaction term with time, there was no substantial change in the hazard for diabetes.
Models using an interaction between transition status and time were fitted.
Multiplicative interactions were evaluated using an interaction term; significance to the logistic model was determined by the log rank test.
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