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We used negative binomial regression (to account for overdispersion) to calculate model-based 10-year incident rate ratios (IRRs) and 95% confidence intervals (CIs) to compare the incident rates of asphyxiation suicides between 2005 and 2014.
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The association of patient- and service-related characteristics with length of stay was analysed using zero-truncated negative binomial regressions to account for the identified overdispersion in count data.
To assess whether these associations could be explained by social interactions, we first tested the extent of correlation between each measure and own-group ethnic density using negative-binomial regression (to account for the skewed distribution of the social interaction variables).
We used binomial regression to calculate RRs adjusted for possible confounders.
Negative binomial regression was used instead of Poisson regression to account for overdispersion in the data.
This possibility must be examined by iterating the negative binomial regression analyses to account for all possible combinations.
We fit a negative binomial regression model to account for statistical overdispersion and to avoid the use of an arbitrary cut-off point for the frequency of ED visits for asthma exacerbation.
41 Analysis of the primary outcome used a three level logistic (2nd order penalised quasi-likelihood extra binomial) regression model to account for clustering at the level of practice, clinician, and patient to produce an odds ratio and associated 95% confidence interval.
We used negative binomial regression to analyze survey data for 9974 middle-aged and older respondents to the Health and Retirement Study in the USA.
We conducted a negative binomial regression to determine any differences in the pre-post periods.In our multivariable analysis, there was a statistically significant decrease in hospital admissions.
We used Cox log-binomial regression to estimate predictors of the use of vascular endothelial growth factor (VEGF) antagonists within 1 year after diagnosis.
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