1. Briefly describe the:
The data collection method and measurements
2. Bivariate methods:
Describe the bivariate techniques employed in data analysis and the results of the bivariate analyses.
In particular, please look at table 3 and identify the correlations between: life satisfaction and depression, perceived social support and depression, functional impairment and depression, functional impairment and life satisfaction, social activities and life satisfaction.
Please indicate if these correlations are significant and the a level (p-value).
3. Define the dependent and independent variables
4. Describe the regression analyses
Which predictors emerged as significant predictors of the outcome(s) in the stage 2 models?
How do these compare to the stage 3 models?
Why do you think the results on the relationship between functional ability and depression, and self rated health and life satisfaction were different in stage 2 and stage 3 results?
How do these results compare with the correlation analyses?
Which factor remained a significant predictor of outcome(s) in the full models (stage 3 models).
Note: Hierarchical regression consists of series of simultaneous multiple regression analyses in which one or more new predictors are added to those used in the previous analysis. The decision concerning which variables to add at each point in the series is made by the investigator.
Required Peer-Reviewed Scholarly Materials:
Cummings, S.M. (2002). Predictors of psychological well-being among assisted-living residents. Health & Social Work, 27(4), 293-303. (Available via ProQuest)
Required Non-Peer-Reviewed Scholarly Materials:
StatSoft, Inc. (2007). Electronic textbook StatSoft-Regression and ANOVA/MANOVA. Retrieved September 23, 2011, from http://www.statsoft.com/textbook/stathome.html
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