All variables with a LRTS of less than 0.2 were put forward into the multivariable model, including recoding using dummy variables of categorical groups appearing to show some evidence of association (Table 4).> The final multivariable model indicated five variables to be significantly associated with the likelihood of a case being classified as critical (Table 5).
There were no significant differences between the model with only level 1 factors and the full model, indicating that level 2 variable effects are independent from level 1 variables effects.
When variables are cointegrated, at least one or all of the error correction terms should be negative and statistically significant in the short-run model indicating showing convergence of the variables in the long run.
For Ddx3a and Ddx3b, M0 was rejected in favor of the alternative model M3 (M3 vs. M0, P < 0.0001), indicating variable selection pressure among sites across these genes.
This model indicates that the variables or interaction variables including soil moisture, wind speed, PM10, temperature, and the monthly dummy variables for March, April, June, July, August, and September explain 87% of the variation in the response variable, monthly average child BPb concentration (R = 0.87, p = 0.0004).
This model indicates that the variables or interaction variables including soil moisture, wind speed, PM10, temperature, and the monthly dummy variables for January, March, April, May explained 61% of the variation in the response variable, monthly average child BPb concentration (R = 0.61, p = 0.0012).
We included an additional variable in the model indicating whether a participant used insulin glargine at baseline (yes/no) and another variable indicating whether a participant used other insulin analogues at baseline (yes/no).
The goodness-of-fit statistics of this model were significantly worse when compared to the four-factor model, indicating that the correlations between observed variables cannot be adequately explained by one factor (see Table 3).
The temperature-dependent resistance was analyzed with the Efros-Shklovskii variable range hopping model, indicating three-dimensional electron hopping conduction in the disordered helical wires.
Finally, we further adjusted for treatment strategy by adding a three group variable to the model indicating whether the patient continued MTX or which arm he/she was randomised to.
