Sentence examples for binomial regression was estimated from inspiring English sources

Conditional fixed effects negative binomial regression was estimated in Stata version 10 to control for these time invariant factors.

The scale parameter for the negative binomial regression was estimated by the square root of the Pearson chi-square/degrees of freedom.

Negative binomial regression was used to estimate the incidence rate ratio (IRR) and its 95%% confidence interval (CI) for count variables.

Negative binomial regression was used to estimate the difference in mean number of missing values between presentation orders and the confidence interval (CI) [ 20]; linear regression was used for HRQoL scores.

Binomial regression was used to estimate the risk ratio, with respective 95% confidence intervals, by taking the risk of infection among those who received antibiotics preoperatively as the numerator and postoperation risk as the denominator.

Similarly, an 8% to a 32% increase was observed when Poisson extension of log binomial regression was carried out to estimate the cumulative effect of repeated lesion-visits on the probability of detectable plasma HIV RNA at the last or 3rd study visit (Table 5, trend p-value  = 0.004).

Negative binomial regressions were then estimated on the number of lifetime, and 12-month chronic conditions and logistic regressions were estimated on the prevalence of pain-related conditions and cardiovascular conditions.

Log binomial regression was used to calculate adjusted PRs.

The overall annual increase, estimated using negative binomial regression, was 3.5%9595% CI, 2.2 4.7) for men and 2.6%9595% CI, 1.4 3.9) for women.

The dispersion parameter estimated by the negative binomial regression was 3.7, with a 95% confidence interval (1.9, 7.5), providing additional evidence that the negative binomial regression was the appropriate model.

Binomial regression was performed using proc genmod, which uses generalized estimating equations to account for cluster sampling.