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The prevalence of each kind of dyslipidaemia has been stratified by the risk factors associated with CVDs in table 3. table 4 represents the results of the multinomial logistic regression modelling for factors associated with single and mixed dyslipidaemia.
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The output properties, i.e., peak strength, break strength, peak elongation, break elongation, etc. were modeled for multi factor optimization.
Associations with 8-week culture conversion were adjusted in multivariate logistic regression models for factors found to be significant in the parent clinical trial.
* Models for factors other than gender and diabetes were fit in subjects without diabetes.
Table 3 shows the full multivariate-adjusted model for factors cross-sectionally associated with RLS.
Table 2 and Table 3 show the final models for factors influencing mortality and survival time.
We attempted to fit an ordered logistic regression model for factors associated with rape perpetration.
SEM was used to test the hypothesized model for factors that influence GTA teaching self-efficacy.
Table 5 shows the final logistic regression model for factors associated with having one or more ERVH.
Associations with treatment outcomes were adjusted in multivariate logistic regression models for factors previously associated with failure and relapse.
Details by Region are reported in Figure 2. Table 2 shows the results of the multiple logistic regression model for factors associated with compensation claims.
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