Sentence examples for multivariable model when from inspiring English sources

This inverse association persisted in the multivariable model when cigarette smoking and outdoor walking activity were adjusted (P trend   = 0.044).

No statistically significant associations were found or any changes in the multivariable model when 'confidence' was added.

MDSC level retained statistical significance in the multivariable model when adjusted by the effects of other prognostic factors.

Although significant in univariable analysis, the association of population density, rainfall, socioeconomic status, and cattle density became nonsignificant in the multivariable model when vegetation density was included (p = 0.66 for population density; data not shown).

In addition, exposure variables of interest were also included in a multivariable model when this factor was statistically significantly associated with either cryptorchidism or hypospadias in the univariate analysis and the factor caused a change by ≥ 15% in the coefficient of other risk factors in the model.

Among these 567 patients, IL6 diplotype was not associated with early events in a univariable model or in a multivariable model when adjusting for tumour size, axillary lymph node involvement, age, and histological grade III (adjusted HR = 1.14; 95% CI 0.62 2.10; P = 0.67).

In addition, the similarity in multivariable models when identified asthma and COPD were included or omitted from the analyses suggests the findings are robust.

On these methodological grounds, LCA supersedes classical statistical models by eliminating part of the endogeneity bias [ 67] introduced in multivariable modeling when indicators of diseases, cognition and disability enter in the model simultaneously.

These results suggest that variables, such as sleep problems and psychiatric distress, may confound the association between wrist pain threshold and CRP, emphasizing the need for multivariable models when studying complex outcomes such as pain.

The normality of residuals and the similar pattern of significance of variables present in the multivariable models when the binary outcome was used imply the suitability of the data to this type of analysis.

In contrast with results from unadjusted analyses (Table 2), only four deployment experiences were significantly associated with GWI in multivariable modeling when all veterans were considered together: wearing uniforms treated with pesticides, taking PB pills, frequently having < 4 hr sleep in a 24-hr period, and being within 1 mile of an exploding SCUD missile.