Sentence examples for binary logistic regression results from inspiring English sources

Table 4 Binary logistic regression results.

However, the binary logistic regression results revealed that poor women owning NHIS are 7% (CI = 1.76 2.87) more likely to make at least four antenatal care visits compared to women in the middle wealth quintile (5%, CI = 2.12 4.76) and rich women (2%, CI = 1.14 4.14).

Descriptive statistics, cross tabulations and binary logistic regression results were generated.

From the binary logistic regression results, the BODE index was an independent predictor for anxious and depressive symptoms after being adjusted for other confounders.

Binary logistic regression results demonstrated that SBT measuring postural sways objectively using a balance board was the only significant predictor of physiological falls risk (P<0.05, odds ratio of 2.12).

The binary logistic regression resulted in an odds ratio to declare a way of comparing whether the probability of a certain event was the same for two groups.

As reflected on the table, the binary logistic regression result shows that age and occupation were accepted in the analysis as significant at less than 5% level while income, education, religion and family structure were not significant.

Binary logistic regression of results from a survey in Ghana based on the Picker questionnaire 1 found that women who were only sometimes treated with respect by MHCPs were 3.6 times more likely to be dissatisfied with childbirth care than those who were always treated with respect [ 110].

Associations between occupational noise exposure dose (continuous noise index), work-related stress, noise annoyance at work and hearing-related symptoms were evaluated in manual sequential binary logistic regression models, results of which are presented in table 3. The calculated noise index ranged from 4.5 to 64 in the study sample.

The binary logistic regression analysis resulted in a significant model (p <.001) with an explained variance (R) of 27.8% (Chi2 (29) = 10407.5).

Analyses using ordinal regression in place of binary logistic regression yielded similar results to the logistic regressions (tables 2– 4).