Sentence examples for binomial regression analysis showed from inspiring English sources

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A negative binomial regression analysis showed the heterozygous males had three times the risk of sperm having a XY content, compared to sperm from wild type males (P = 0.024).

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).

*Low = HKD 6,110 97,180; Moderate = HKD98,940 529,900; High = HKD532,242 993,300 CI, confidence interval Results from negative binomial regression analysis showed that significantly greater number of peer-reviewed papers published was found for projects with high (HKD 532,242 – HKD 993,300) funding awards (mean difference 0.76 compared with projects with low funding awards, 95% CI 0.19 1.33).

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Multiple binomial logistic regression analysis showed that serum TAC levels were associated with 30-day mortality, after controlling for Glasgow Coma Scale and age (odds ratio 1.92; 95 % confidence interval 1.201 3.072; p = 0.006).

Binomial logistic regression analysis showed that haplogroup T and systolic blood pressure are risk factors for a high degree of morbid obesity, namely, BMI > 45 kg/m and in fact together account for 8% of the BMI.

Multiple binomial logistic regression analysis showed that serum SP levels >299 pg/ml were associated with 30-day mortality when we controlled for APACHE II score and Marshall computed tomography lesion classification (odds ratio (OR) =5.97; 95% CI, 1.432 to 24.851; P =0.01) and for GCS score and age (OR =5.71; 95% CI, 1.461 to 22.280; P =0.01).

Binomial multivariate logistic regression analysis showed that only ASA score is an independent risk factor for in-hospital mortality.

Piecewise regression analysis showed similar results.

Regression analysis showed similar differences.

Logistic regression analysis showed the similar patterns.

Table 3 > -wrap-foot> shows the univariate log binomial regression analysis of prognostic risk factors for IP including age, diagnosis, sex, transplant type, dose rate, GVHD and grade of GVHD.

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