Correlational research

1. Correlational research Correlational studies Regression and multiple regression Factor analysis and cluster analysis

2. Correlational research • Measured vs. manipulated variables • Ex post facto studies • Categorical vs continuous variables

3. Methods of correlation • Scatterplots • Correlation coefficients • Continuous: Pearson r • Categorical: • Spearman r for ranked data on one variable • Kendall’s Tau for two ranked variables • Cramer’s statistic, f , for two dichotomous variables • Point biserial for one continuous variable and one naturally dichotomous variable • Biserial for one continuous variable and one forced dichotomy • Tetrachoric for two forced dichotomies

4. Why use correlational designs? • When it is impossible or unethical to manipulate the independent variable. • When investigating new ideas • When controlled study would threaten external validity • When we want to predict, using regression

5. Conducting correlational studies • Control threats to validity • Control extraneous variables • Use valid, reliable, and sensitive measures • Resist the temptation to draw causal conclusions.

6. Correlational studies are also used for • Reliability assessment: .80 minimum • Inter-rater reliability • Test-retest reliability • Equivalent forms reliability • Split-half or odd-even reliability

7. Validity assessment • Face validity • Convergent validity • Divergent or discriminant validity • Criterion validity • Concurrent validity • Predictive validity

8. Methods of regression • Regression equations • Linear regression • Multiple regression • Curvilinear regression

9. Uses of regression • To predict • Discriminant analysis • Partial correlation • Factor analysis