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Bivariate techniques were used to demonstrate whether there is a significant difference between men and women with respect to selected socio-economic and demographic variables.
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In order to clearly show gender inequality and women's empowerment in the country, bivariate and multivariate techniques were used based on the variables supplied in both Ethiopian Demographic and Health Survey (EDHS) 2005 and 2011.
This study sought to fill this knowledge gap by examining the level of understanding of heart attack and stroke symptoms among rural adults in comparison to non-rural adults living in the U.S. Bivariate and multivariate techniques were used to analyze a multiyear Behavioral Risk Factor Surveillance Survey (BRFSS) heart attack and stroke module database.
Bivariate and multivariate analysis techniques were used during analysis.
In addition to bivariate analysis, multivariate analysis techniques were used to assess construct validity.
Bivariate correlation and moderated regression techniques were used to analyze the data collected.
Bivariate and multivariate (logistic regression) analysis techniques were used to identify determinants of morbidity and disability among Canadian women as compared with men using CCHS data.
Multiple post-processing techniques are used: quantile-to-quantile transform, linear regression with an assumption of bivariate normality and logistic regression.
In [6], a similar technique is used, but the bivariate a priori pdf of the clean image of type is considered.
Bivariate descriptive analysis coupled with binary logistic regression estimation technique was used to analyse the data.
While bivariate techniques are becoming more common in meta-analyses of medical diagnostic tests, they have not been frequently used outside that field.
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