Multicollinearity and misleading statistical results
نویسندگان
چکیده
منابع مشابه
Misleading Statistical Studies
Large statistical studies in the social sciences, including one-off or repeated cross-sectional surveys, time-series surveys and cohort longitudinal research, offer important numeric evidence for policy making. Although single studies rarely occasion dramatic policy shifts, statistical research findings can affect policy debate, even if not always directly or openly. At best, these studies reve...
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The authors fail to control for relevant "third" variables that could easily explain the weak correlations that they find. Family violence exposure for instance, peer group influences, certainly genetic influences on aggressive behavior are just a few relevant variables that ought either be controlled or at minimum acknowledged as alternate causal agents for (very small) link between video game...
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If there is no linear relationship between the regressors, they are said to be orthogonal. Multicollinearity is a case of multiple regression in which the predictor variables are themselves highly correlated. If the goal is to understand how the various X variables impact Y, then multicollinearity is a big problem. Multicollinearity is a matter of degree, not a matter of presence or absence. In...
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OBJECTIVE In this study, the capability of statistical analysis indices to characterize static automated visual fields (VFs) accurately in cases of far-advanced glaucoma was assessed. DESIGN Retrospective observational case series. PARTICIPANTS Sixteen eyes of 15 patients with end-stage glaucoma and evidence of collapse of VF statistical analysis indices were included in the study. METHOD...
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ژورنال
عنوان ژورنال: Korean Journal of Anesthesiology
سال: 2019
ISSN: 2005-6419,2005-7563
DOI: 10.4097/kja.19087