Sentence examples for models not adjusting from inspiring English sources

GEE models not adjusting for the pre-specified factors gave similar results (data not shown).

Therefore, we presented the results from the conditional logistic regression models not adjusting for these potential confounders.

However, models not adjusting for chronic conditions, which are most likely to be plagued by endogeneity, did not alter the primary study findings.

In multivariate models not adjusting for adherence (middle column, Table 2) the aHR for AIDS death in black vs. white women was 2.14 (95% CI 1.30, 3.50; P = 0.003).

For males, suicide risk was highest in the lowest socio-economic status group (OR = 3.08, 95%CI 1.21-7.82, P = 0.018), followed by the middle socio-economic status group (OR = 1.58, 95%CI 0.61-4.09, P = 0.350) compared to the highest socio-economic status group (OR = 1.00), in models not adjusting for intermediary mental disorder variables (P for linear trend = 0.015) (Table  2).

Adjustment for parental education resulted in slightly lower risk estimates overall, both for paternal and for maternal occupational exposure to solvents, when compared to models not adjusted for education.

In these instances, models not adjusted for neighborhood median household income in associations of walkable built environment variables with BMI z-score are underadjusted, and neighborhood median household income is a qualitative confounder.

Of the covariates, educational level and having late complications were significantly related to follow-up glycaemic control in models not adjusted for HbA1c baseline and time, and education remained significant when adjusting for the baseline HbA1c and time in all models.

The dog × pollutant interaction effect estimates were generally stronger after adjusting for pollutant interactions with parental history of asthma and with ethnicity, and the interaction of dog with PM2.5, which was not significant in models not adjusted for these additional covariates, became significant.

Therefore we will also run the following model, not adjusting for number of visits, to evaluate a general trend of total dose, (1.3) log i t Y i = β 0 + β 1 T o t a l D o s e i + β 2 T o t a l D o s e i 2 + α Z i If the quadratic term is not statistically significant then this would indicate no thresholding effect.

In the model not adjusted for potential confounding factors TMD groups was included as dichotomous dummy variables with non-TMD as the reference group.