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Logistic regressions were used to explore determinants of responses in the EQ-5D dimensions, and robust linear regression was used to explore determinants of the EQ-5D index.
Bivariate and multivariate logistic regression was used to explore determinants of smoking during pregnancy.
Multivariable logistic regression was used to explore determinants of mobility using 'residential move' as the binary outcome; variables were entered into the model simultaneously.
A stepwise multiple regression analysis was used to explore determinants for the serum and milk levels of contaminants using a forward backward stepwise regression model (F-statistic to enter and stay in the model with a p-value of < 0.25).
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Univariate analyses were used to explore the determinants of attendance at ANC, the association between ANC and other behavioural decisions and the determinants of the two key outcomes: pregnancy outcomes and birthweight.
Multiple linear regression analysis was used to explore the determinants of IMR using possible predictor variables.
Multiple linear regression analysis (MLRA) was used to explore the determinants of infant mortality.
Multivariable regression models were used to explore the determinants of out-of-pocket expenditures.
Multivariate regression analysis was used to explore the determinants of variability in unit costs using data for 44 countries with a total of 984 observations.
A multivariate logistic regression model was used to explore the determinants of reported difficulty accessing specialist care when needed in the prior year.
* Spearman's Rank Correlation (non-normal data) ** r is a measure of the linear relationship between IMR and the independent variables † Statistically significant at p < 0.05 Multiple logistic regression analysis was used to explore the determinants of IMR.
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CEO of Professional Science Editing for Scientists @ prosciediting.com