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Correlational research. Correlational studies Regression and multiple regression Factor analysis and cluster analysis. Correlational research. Measured vs. manipulated variables Ex post facto studies Categorical vs continuous variables. Methods of correlation. Scatterplots
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Correlational research Correlational studies Regression and multiple regression Factor analysis and cluster analysis
Correlational research • Measured vs. manipulated variables • Ex post facto studies • Categorical vs continuous variables
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
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
Conducting correlational studies • Control threats to validity • Control extraneous variables • Use valid, reliable, and sensitive measures • Resist the temptation to draw causal conclusions.
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
Validity assessment • Face validity • Convergent validity • Divergent or discriminant validity • Criterion validity • Concurrent validity • Predictive validity
Methods of regression • Regression equations • Linear regression • Multiple regression • Curvilinear regression
Uses of regression • To predict • Discriminant analysis • Partial correlation • Factor analysis