A survey of variable selection methods in two Chinese epidemiology journals

Abstract

BackgroundAlthough much has been written on developing better procedures for variable selection, there is little research on how it is practiced in actual studies. This review surveys the variable selection methods reported in two high-ranking Chinese epidemiology journals.MethodsArticles published in 2004, 2006, and 2008 in the Chinese Journal of Epidemiology and the Chinese Journal of Preventive Medicine were reviewed. Five categories of methods were identified whereby variables were selected using: A - bivariate analyses; B - multivariable analysis; e.g. stepwise or individual significance testing of model coefficients; C - first bivariate analyses, followed by multivariable analysis; D - bivariate analyses or multivariable analysis; and E - other criteria like prior knowledge or personal judgment.ResultsAmong the 287 articles that reported using variable selection methods, 6%, 26%, 30%, 21%, and 17% were in categories A through E, respectively. One hundred sixty-three studies selected variables using bivariate analyses, 80% (130/163) via multiple significance testing at the 5% alpha-level. Of the 219 multivariable analyses, 97 (44%) used stepwise procedures, 89 (41%) tested individual regression coefficients, but 33 (15%) did not mention how variables were selected. Sixty percent (58/97) of the stepwise routines also did not specify the algorithm and/or significance levels.ConclusionsThe variable selection methods reported in the two journals were limited in variety, and details were often missing. Many studies still relied on problematic techniques like stepwise procedures and/or multiple testing of bivariate associations at the 0.05 alpha-level. These deficiencies should be rectified to safeguard the scientific validity of articles published in Chinese epidemiology journals.

Step away from stepwise

“…A survey of four leading epidemiologic journals found that 20% of the articles published in 2008 used stepwise regression [14]. A study of articles published between 2004 and 2008 in two leading Chinese epidemiology journals found that, of the articles using multiple regression models, 44% used stepwise procedures [15].…”

Prescription-Drug-Related Risk in Driving

“…5,7,8 We report the application of lasso shrinkage logistic regression to the analysis of the database described in Orriols and colleagues. Lasso-related methods provide a useful tool, although one that remains unfamiliar to most epidemiologists.…”

SMART Population Screening and Management in Qatar

“…As a result, for our analysis we decided to include all hypothesized independent variables of interest in the model without using bivariate analysis or other techniques to screen the variables for best fit. Liao H & Lynn H [6] mentioned, "the screening of variables using significance testing runs the risk of increased type I errors of the predictors in the multivariable model, and should instead be based on evaluation of background knowledge. In addition, using bivariate associations to select variables for multivariable analysis ignores potential confounding or co-linearity between the independent variables, implying that a non-significant variable in the bivariate analysis can in fact be a significant variable in the multivariable analysis".…”