Suicide Statistical Analysis of Suicide Article Review

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Here, the dependent variable is identified as the proclivity toward suicide. The researchers identify four independent variables due for measurement. These are identified as psychological distress, hopelessness, drug abuse, and relationship discord. (Kaslow et al., p. 13)

The study collected data using interviewing techniques that would occur within a 24 to 72 window of the subject's hospital admission. Findings would be measured in the categories of Psychological Risk Factor Variables and Interpersonal Risk Factor Variables. These would rely, respectively, on the 53-item Brief Symptom Inventory author by Derogatis & Spencer (1983) and the Locke-Wallace Martial Adjustment Tests (1959).

Multivariate Analysis would ultimately prove an appropriate strategy for statistical assessment for its capacity to incorporate a wide range of measurements into a single analytical discussion. According to the study, "A multivariate logistic regression model was con- structed that included the significant univariate risk factors (three demographic variables, four psycho- logical risk factors, and five interpersonal risk fac- tors). By using the combination of these 12 variables, suicide attempt status could be predicted correctly 77% of the time. " (Kaslow et al., p. 16) as the findings of the research ultimately show, this model would help to produce a statistically reliable mode of forecasting suicidal risk and, therefore, an effective response to the research question which inquires upon the connection between certain risk factors and the proclivity toward suicide.

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As with the study by Kaslow et al., the study by Lincoln et al. (2012), taken from the April e-Pub edition of Social Psychiatry and Psychiatric Epidemiology and entitled "Suicide, negative interaction and emotional support among black Americans" seeks to answer a primary research question connecting certain risk factors among African-Americans with a propensity toward suicide. Likewise, the study sets out to use multivariate logistical regression analysis in order to explore the proportions of this perceived correlation.

Here, the dependent variable is, rather than the status of the presenting individual's proclivity toward suicide, the presence of suicide behaviors and ideation. The study incorporates a significantly larger sample and one with far fewer variable controls. Accordingly, 3,570 African-Americans and 1,621 Caribbean blacks age 18 or older were interviewed for data-gathering regarding suicide behaviors and ideation without distinction of gender or age division. The two independent variables are identified as negative interaction and emotional support. Utilizing the National Survey of American Life as a baseline measurement, the multivariate analysis would prove particularly valuable for establishing causality of the dependent variable in both independent variables while simultaneously demonstrating that the Caribbean group tested as more vulnerable to this causality than the African-American in both cases.

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