This paper demonstrates the first use of shrinkage logistic regression as a pattern discovery method in international adverse drug reaction surveillance. This novel method is compared to bivariate pattern discovery, the standard approach in the application domain. Our results show that regression can eliminate false positives and false negatives due to the impact of other covariates, and that i...

The common practice of collapsing inherently continuous or ordinal variables into two categories causes information loss that may potentially weaken power to detect effects of explanatory variables and result in Type II errors in statistical inference. The purpose of this investigation was to illustrate, using a substantive example, the potential increase in power gained from an ordinal instead...

Methods This is a secondary database analysis of the Project RED dataset (N=623) identifying the sociodemographic characteristics as well as underserved patient factors associated with CAM use. We used descriptive statistics, bivariate, and multivariate logistic regression. We used multivariate logistic regression models for each outcome (any CAM use, CAM provider delivered therapies, and relax...

the purpose of this study is presenting a model forecasting financial crisis in tehran stock exchange listed companies. to do this, productive firms that had been accepted in tehran stock exchange between 2002 and 2009, were selected as the study sample. first the independent variables were obtained based on financial ratios and then based on article 141 of the law of commerce, the insolvent an...