Assuming that we modify e1 as e 1 ′ = s s o d < { o r d e r, g o o d s, i n v o i c e }, { a l i c e, b o b }, 2 >, or modify f3 as f 3 ′ = s a < { o r d e r, g o o d s }, { a l i c e, b o b }, 2 >.
Briefly, we proposed a 3-step strategy: – Fit an imputation model assuming ignorable MVs; – Modify the imputation model by adding a parameter (expressed as the odds ratio comparing the odds of a response category among subjects with MV with those without MV for categorical variables; as the difference in expected values for continuous variables); – Impute MVs under the scenario thus specified.
You can just include it in your program (you don't even have to acknowledge this use; we'll assume it), or modify it should you like (again, no acknowledgement is necessary).
To constrain aftershock locations using a single station, we estimate the backazimuth from the P-wave particle motion and the epicentral distance from the differential travel time of S- and P-wave, assuming a modified CRUST 2.0 layered velocity structure (Bassin 2000).
In this model, different types of immune response are assumed to modify the virus parameters δ, c, β and p. All the parameters (and consequently the immune response) are assumed to be constant in time.
RARB is assumed to modify the expression levels of four genes: ELF3, NCOA2, ZNF42, and CDKN1A.
The intervention was assumed to modify only the incidence of disease in healthy participants At Risk.
Computer-aided detection was assumed to modify CONV report only in the sense of additional recall.
Under the above model, the polygenotype is assumed to modify the disease risk in BRCA1 and BRCA2 carriers.
The intervention was assumed to modify only the incidence of physical disease in healthy participants at risk.
Genetic susceptibility for islet autoimmunity is well documented (2), and environmental factors are assumed to modify the genetically defined risk of developing islet autoantibodies (1, 3).
