Biserial
Correlation between continuous and ordinal variables
The biserial correlation is used to assess the relationship between an ordinal outcome and a continuous outcome. Biserial correlations are most often used in social sciences when validated instruments are compared to non-validated instruments. Biserial correlations can be further be used when establishing the association between variables before performing multivariate analysis. Always check for normality of the continuous outcome and the ordinal outcome when conducting biserial correlations.
The Venn diagram below depicts the correlation of an ordinal variable and a continuous variable. Biserial is the correlation test used when testing the relationship between an ordinal variable and a continuous variable.
The steps for conducting a biserial correlation in SPSS
1. The data is entered in a within-subjects fashion.
2. Click Analyze.
3. Drag the cursor over the Correlate drop-down menu.
4. Click on Bivariate.
5. Click on the continuous outcome variable to highlight it.
6. Click on the arrow to move the variable into the Variables: box.
7. Click on the ordinal outcome variable to highlight it.
8. Click on the arrow to move the variable into the Variables: box.
9. Click OK.
2. Click Analyze.
3. Drag the cursor over the Correlate drop-down menu.
4. Click on Bivariate.
5. Click on the continuous outcome variable to highlight it.
6. Click on the arrow to move the variable into the Variables: box.
7. Click on the ordinal outcome variable to highlight it.
8. Click on the arrow to move the variable into the Variables: box.
9. Click OK.
The steps for interpreting the SPSS output for a biserial correlation
1. In the Correlations table, match the row to the column between the two variables. The Pearson Correlation is the actual correlation value that denotes magnitude and direction, the Sig. (2-tailed) is the p-value that is interpreted, and the N is the number of observations that were correlated.
If the p-value is LESS THAN .05, then researchers have evidence of a statistically significant bivariate association between the two variables.
If the p-value is MORE THAN .05, then researchers have evidence that there is not a statistically significant association between the two variables.
Higher coefficients denote a stronger magnitude of relationship between variables. Smaller coefficients denote weaker relationships.
Positive correlations denote a relationship that travels at the same trajectory. As one value goes up, then the other value goes up. Also, as one value goes down, then the other value goes down too.
Negative correlations denote a relationship that travels in different directions. As one value goes up, the other value goes down. Also, as one value goes down, then the other value goes up.
If the p-value is LESS THAN .05, then researchers have evidence of a statistically significant bivariate association between the two variables.
If the p-value is MORE THAN .05, then researchers have evidence that there is not a statistically significant association between the two variables.
Higher coefficients denote a stronger magnitude of relationship between variables. Smaller coefficients denote weaker relationships.
Positive correlations denote a relationship that travels at the same trajectory. As one value goes up, then the other value goes up. Also, as one value goes down, then the other value goes down too.
Negative correlations denote a relationship that travels in different directions. As one value goes up, the other value goes down. Also, as one value goes down, then the other value goes up.
Click on the Download Database and Download Data Dictionary buttons for a configured database and data dictionary for biserial correlations. Click on the Adjusing for Multiple Comparisons button to learn more about Bonferroni, Tukey's HSD, and Scheffe's test. Click on the Validation of Statistical Findings button to learn more about bootstrap, split-group, and jack-knife validation methods.
Statistician For Hire
DO YOU NEED TO HIRE A STATISTICIAN?
Eric Heidel, Ph.D. will provide statistical consulting for your research study at $100/hour. Secure checkout is available with PayPal, Stripe, Venmo, and Zelle.
- Statistical Analysis
- Sample Size Calculations
- Diagnostic Testing and Epidemiological Calculations
- Psychometrics