According to the multiple regression model, none of the independent variables are consistently statistically significant predictors of the error score across each of the separate samples and the combined sample (see Table 2).
Stepwise multiple regression found none of the possible explanatory variables body condition, body size and hatching date to be related to variation in tarsus R/G values.
In multiple regression analysis, none of the features, which were significantly associated with disease-free survival in the univariate analysis, remained statistically significantly associated with disease-free survival after correction for covariates.
To this end, we used two models (see statistical analyses): model 1 included all variables listed in Table 1 and was therefore highly redundant; model 2 included, at each step, only variables selected by a stepwise multiple regression procedure (IFG: none; IGT: age; newly diagnosed diabetes: plasma glucose; 0 9 years: age and A1C; 10 19 years: age; ≥20 years: age and A1C).
None of the multiple regression models using combinations of tree variables was significant nor was site significant as an explanatory variable when included in regression models predicting MOEL.
Using multiple regression (all independent variables in combination), none of the variables acted as predictors of reintubation (P = 0.25).
However, when these were entered into a multiple regression analyses that controlled for pre-treatment levels, none remained a significant predictor of the post-treatment and follow-up symptomatic status.
In the simple models smoking, high home life demands and asthma were risk factors and breakfast regularly was a health factor, but none of these were statistically significant in the multiple regression model (Table 5).
Moreover, none of the other determinants of tHcy in the multiple regression model (folate, vitamin B12) showed a predictive value at a P level<0.10).
Although several of the prognostic factors were correlated with the symptomatic outcome, none remained a significant predictor when entered into a multiple regression model that included the pre-treatment symptom levels.
