Sentence examples for binomial regression analysis and from inspiring English sources
Demographic and technical risk factors for these complications were analysed sequentially in a binomial regression analysis and subsequently in a multivariable model.
The effect of sealant on DMFS was evaluated with negative binomial regression analysis and it was found that sealants reduced caries prevalence by 11% in the 12-year-old group (not statistically significant) and by a statistically significant level of 24% in the 15-year-old group (table 5).
To assess potential mediation, the relationship between VF loss or CS and MVPA was assessed using negative binomial regression analysis via Baron and Kenny's step-wise approach [ 48].
Baseline characteristics and laboratory test results were described and the binomial regression analysis was conducted to investigate the relationship between insulin resistance and coronary atherosclerotic plaque progression.
In addition, we analyzed factors associated with risk of newborn deaths (still births and neonatal deaths) using log binomial regression analysis, where characteristics of newborn deaths (still births and neonatal deaths) and those of survivors (neonatal near miss and babies with no or minimal complications) were compared and adjusted relative risks computed.
A total of 2,386 mRNAs were significantly dysregulated in miR-dKO round spermatids (negative binomial regression analysis, p<0.05), including 861 downregulated, and 1,525 upregulated mRNAs (Fig. 6A; supplementary material Table S4).
A negative binomial regression analysis was used to investigate trends and compare rates across years, sex and age groups (0 4, 5 11, 12 15 years).
We utilized logistic regression analysis to compare the odds of initiating outpatient care among women and men and standard negative binomial regression analysis to assess the intensity of utilization.
When country and frequency were mutually adjusted for in a multiple binomial regression analysis, the effect of country declined and became non-significant, while the effect of frequency remained almost unchanged.
Multivariate negative binomial regression analysis showed that male sex, older age group, and African American and Hispanic race/ethnicities were significantly associated with an increased risk for initial hospitalization (p<0.0001 for all) (Table 4).
