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Logistic Regression Analysis

Logistic Regression Analysis
Lacourse, Claes, and Villeneuve (2001) carried out a study to see whether a love of heavy metal could predict suicide risk. Eric Lacourse and his colleagues used questionnaires to measure several variables: suicide risk (yes or no), marital status of parents (together or divorced/separated), the extent to which the person’s mother and father were neglectful, self-estrangement/powerlessness (adolescents who have negative self-perceptions, are bored with life, etc.), social isolation (feelings of a lack of support), normlessness (beliefs that socially disapproved behaviors can be used to achieve certain goals), meaninglessness (doubting that school is relevant to gain employment) and drug use. In addition, the authors measured liking of heavy metal; they included the sub-genres of classic (Black Sabbath, Iron Maiden), thrash metal (Slayer, Metallica), death/black metal (Obituary, Burzum) and gothic (Marilyn Manson). As well as liking, they measured behavioral manifestations of worshipping these bands (e.g., hanging posters, hanging out with other metal fans) and what the authors termed ‘vicarious music listening’ (whether music was used when angry or to bring out aggressive moods). They used logistic regression to predict suicide risk from these variables for males and females separately.
Upon running a logistic regression analysis, you obtain the following output:
1) Does listening to heavy metal music (Variables: Liking Metal Music, Vicarious Listening, Worshipping) predict suicide risk in women?
2) What factors predict suicide risk in women? 

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