Fischer's exact test No significant confounders were identified by stratified analysis and ORs, adjusted for confounding by Mantel Haenszel procedure, were not significantly different from the crude ORs.
Attempts were made to control, by design or statistical analysis, for significant confounders.
When we investigate univariate traits, such as richness or taxa abundances, for most of the significant confounders, we use linear model/generalized linear models to remove their "effect" and keep the residues for the genetic analysis.
The final model contained 1 animal-based parameter and 3 risk factors related to lying as well as 1 nutritional animal-based parameter, while correcting for the significant confounders parity and data subset.
Similarly, we identified gender, current physical activity, alcohol consumption, calcium intake, and BMI as significant confounders for bone turnover markers.
There were no significant confounders.
We used a backward selection procedure to identify significant confounders.
The number of significant confounders in neuropsychological testing is high.
The multivariate models included both significant predictors and significant confounders.
Model 1 was unadjusted, model 2 was adjusted for significant confounders only and model 3 was adjusted for significant confounders and low back pain.
We concluded that age and parity were not significant confounders and presented results bivaraite associations.
