Sentence examples for binomial regression to control from inspiring English sources

Because of uneven distribution of baseline characteristics, we performed analysis of covariance with negative binomial regression to control for baseline differences [ 24].

We used log binomial regressions to control for any potential confounders.

Logistic regression was used, instead of binomial regression, to avoid convergence issues when controlling for many confounding variables.

We used logistic binomial regression to estimate relative risks (RR) and control potential confounders.

We used binomial regression to calculate RRs adjusted for possible confounders.

After testing different models, we used negative binomial regression to adjust rural and urban cases.

We used logistic regression and zero truncated negative binomial regression to model the zero and count processes, respectively.

Negative binomial regression models controlling for sex, age group, and race/ethnicity were also used to test for statistical significance of the trends in initial hospitalization in the endemic and less endemic regions.

In multivariate binomial regression models controlling for covariates, the association was attenuated but still present.

Associations between environmental and virological (influenza A, influenza B and respiratory syncytial virus (RSV)) exposures and IMD incidence were evaluated using negative binomial regression models controlling for seasonal oscillation.

In adjusted analyses, we estimated negative binomial regression models that controlled for patient level and physician level characteristics and included a random effect for physician.