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We applied adjusted negative binomial regression models to compare the sperm aneuploidy outcomes of exposed men to unexposed men.
11 We used negative binomial regression models to estimate suicide trend in each country between 2000 and 2007.
We used the prediction sample data to fit negative binomial regression models to obtain parameter coefficients of incidence for the sociodemographic and socioenvironmental factors included in each model.
We used count data models such as Poisson and negative binomial regression models to compare the LOS between the HI and the MA group.
We used negative binomial regression models to estimate the unadjusted and adjusted relative risks (RR) with corresponding 95%% confidence intervals (CI) for tooth loss as an outcome.
We used zero-inflated negative binomial regression models to examine the associations of demographic and clinical characteristics with the rates of measurement during follow-up.
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We used a multivariable negative binomial regression model to evaluate the association between salivary cotinine and hospital admissions.
We built a multivariable log binomial regression model to examine the simultaneous effect of race, sex, insurance, age, and age group on CRS.
To choose criterion variables that are predictive of the designated use, I utilized statistical models (structural equation models, multiple regression, and binomial regression model) to link the measured water quality variables to expert elicited categories of eutrophication and the designated uses.
We therefore used a negative binomial regression model to explain the variability of the number of consultations.
To account for variations in the surveillance area, FoodNet uses a main-effects log-linear Poisson (negative binomial) regression model to assess changes in incidence rates (1 ).
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