Week_13_14_corr_mult_reg_rev_4_19_08

Week_13_14_corr_mult_reg_rev_4_19_08 - 1 SAN JOS STATE...

Info iconThis preview shows pages 1–4. Sign up to view the full content.

View Full Document Right Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: 1 SAN JOS STATE UNIVERSITY College of Social Work S. W. 242 Spring 2008 Edward Cohen Week 12, 4/11/08 & Week 13, 4/18/08 Correlation and Multiple Linear Regression I. What is correlation ? Correlation tests the relationship between a continuous independent variable and a continuous dependent variable . Correlation tests produce an r value and a p value . The r value is always between -1 and +1, and indicates the degree to which the two variables are related. A negative r value indicates that as the value of one variable increases, the value of the other variable decreases (referred to as a negative correlation) Example of a graph of a negative correlation Variable 2 40.00 35.00 30.00 25.00 20.00 Variable 1 40.00 35.00 30.00 25.00 20.00 2 A positive r value indicates that as one variable increases, the other variable also increases (referred to as a positive correlation) Example of a graph of a positive correlation Variable 2 40.00 35.00 30.00 25.00 20.00 Variable 1 40.00 35.00 30.00 25.00 20.00 An r value of zero indicates no relationship between variables Example of a graph indicating no correlation between variables Variable 2 70.00 65.00 60.00 55.00 50.00 45.00 40.00 Variable 1 40.00 35.00 30.00 25.00 20.00 3 Research Scenario: Correlation In the general child population, a number of contextual factors have been linked to emotional problems in children and youth, including: 1) low income, 2) negative parenting behavior (i.e. hostile or coercive parenting), 3) family conflict (including family violence and verbal abuse), and 4) low self-efficacy of the childs primary caregiver (i.e. the extent to which the primary caregiver feels mastery over her/his life) Although the relationship between 1) income, 2) parenting, 3) family conflict, and 4) primary caregiver self-efficacy and childrens emotional problems has been established in the general child population, much less is known about how these four factors might contribute to emotional problems among children in immigrant families. You are interested in testing the relationship between income, parenting behavior, family conflict and primary caregiver self-efficacy among a randomly selected sample of 379 children of immigrant parents in Los Angeles County. Within each family one primary caregiver and one child is interviewed with a structured interview format. This sample includes children ages 9 to 15. First, we will look at the separate bivariate relationships between each independent variable and the dependent variable. Then we will include all variables in a simultaneous multivariate model (see 12, Multivariate Statistics). Bivariate Analyses 1) Identify the independent variables and their levels of measurement There are four continuous independent variables in this research scenario: 1) Independent Variable: Poverty , measured with income-to-needs ratio, which is a ratio that takes the total family income and divides it by a poverty threshold determined by the federal government. An income-to- needs ratio of 1 means that the familys income is exactly proportional to 4...
View Full Document

Page1 / 24

Week_13_14_corr_mult_reg_rev_4_19_08 - 1 SAN JOS STATE...

This preview shows document pages 1 - 4. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online