Sentence examples for binomial regression for the from inspiring English sources

In view of overdispersion in the data, we used negative binomial regression for the continuous component with logistic regression for the binary component.

3) We describe independent associations between diagnoses and impairments and disability using zero inflated binomial regression for the WHODAS total score (correcting for zero inflation and overdispersion) and Poisson regression for the dichotomous outcome of 15 or more disability days in the last month.

We analysed secondary outcomes by using Cox proportional hazards for mortality, logistic regression for institutionalisation and falls, negative binomial regression for the number of secondary care contacts, and analysis of covariance for the EQ-5D score and log transformed General Health Questionnaire 12 score.

Using a negative binomial regression for crash frequency estimation, the average annual daily traffic per lane, the interaction between the posted speed limit change and the existence of an off-ramp, and the interaction between the travel lane number change and the pavement surface material change were found to increase the likelihood of vehicle to vehicle crashes under rainfall.

The negative binomial regression for condoms was used to examine the impact of the intervention on condom sales by examining the interaction of study group by time.

SAS 9.4 (SAS Institute, Inc., Cary, NC) was used for all statistical analyses except for negative binomial regression, for which we used the STATA 12 package (Stata Corp LP, College Station, TX).

In the negative binomial regression for condoms, there was an overall significant interaction between the study group and time variables (p = 0.003), indicating an effect of the intervention, and there was a significant slowing in the drop of sales at time 3 in comparison with time 1 (p < 0.001).

Table 2 shows the results of negative binomial regression for factors associated with follow-up PSQI scores.

We used negative binomial regression for duration of symptoms (because of overdispersion), multiple linear regression for the severity of symptoms, logistic regression for antibiotic use and repeat consultations, and Cox regression for time to repeat consultation.

The resulting factors, plus recorded site-level biodiversity, were then used as predictor variables in a confounder-adjusted binomial regression for preference for site conservation.

Study characteristics were examined using chi-square and log binomial regression for hypothesis-specific testing.