Exploring the Relationship Between Socioeconomic Status, Age, and Optimism on Longevity in Cancer Patients

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Running head:MODULE 7 PROBLEM SET1Module7Problem Set

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MODULE 7 PROBLEM SET2Module7Problem Set:Optimism and LongevityA cancer specialist from the Los Angeles County General Hospital (LACGH) rated patientoptimism in 20-to 40-year-old male patients with incurable cancer in 1970. In 1990, theresearcher examined hospital records to gather the following data:Socioeconomic status (1–7 rating of occupation; higher ratings indicate higher levels ofSES)Age in 1970Optimism in 1970 (1–100 rating, higher scores indicate higher levels of optimism)Longevity (years lived after the 1970 diagnosis)Using the SPSS data file for Module 7 (located in Topic Materials), calculate a simultaneousmultiple regression with SES, age, and optimism as the independent variables and longevity asthe dependent variable.1.Do the independent variables correlate statistically significantly and practically withthe dependent variable?The ANOVA table shows thatF(3, 240) = 41.684 and is significant atp< .001.This indicates that the combination of the predictorvariablesof SES,Age,andOptimismsignificantly predictsthe criterion variableLongevity(Leech, Barrett, & Morgan, 2015).ANOVAaModelSum of SquaresdfMean SquareFSig.1Regression1663.1873554.39641.684.000bResidual3192.02624013.300Total4855.213243a. Dependent Variable: Years Lived after Diagnosisb. Predictors: (Constant), Optimism, Age, Socioeconomic Status

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MODULE 7 PROBLEM SET3Also, Leech and colleagues (2015) noted the importance of the Coefficients tablebecause “it provides the standardized beta coefficients, which are interpreted similarly tocorrelation coefficients or factor weights. Thetvalue and significance opposite eachindependentvariable indicatewhether that variable is significantly contributing to theequation for prediction of the dependent variable from the whole set of predictors”(p.116). Therefore, it can be observed that the predictor variable of Optimism is statisticallysignificant, whereas the predictor variables of Socioeconomic Status and Age are not.CorrelationsYears Livedafter DiagnosisSocioeconomicStatusAgeOptimismPearsonCorrelationYears Lived after Diagnosis1.000.369-.332.573Socioeconomic Status.3691.000-.290.520Age-.332-.2901.000-.431Optimism.573.520-.4311.000Sig. (1-tailed)Years Lived after Diagnosis..000.000.000Socioeconomic Status.000..000.000Age.000.000..000Optimism.000.000.000.NYears Lived after Diagnosis244244244244Socioeconomic Status244244244244Age244244244244Optimism244244244244CoefficientsaModelUnstandardized CoefficientsStandardizedCoefficientstSig.CorrelationsBStd.ErrorBetaZero-orderPartialPart1(Constant)3.7732.1311.770.078Socioeconomic Status.236.164.0891.441.151.369.093.075Age-.073.044-.097-1.675.095-.332-.107-.088Optimism.175.023.4857.433.000.573.433.389a.Dependent Variable: Years Lived after Diagnosis

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