# One-Way ANCOVA

An One-Way ANCOVA is an ANCOVA Parametric Statistical Test that compares the means two or more independent samples, groups, interventions or scores by evaluating the differences in adjusted means for the covariate.

**Example(s):**- STATA Support One-Way ANCOVA example(s): http://campusguides.lib.utah.edu/c.php?g=160853&p=1054196

**Counter-Example(s):****See:**ANOVA, One-Way Hypothesis Test, Statistical Test, Variance, Covariance, Independent Variable, Dependent Variable, F Statistics, F-Test, T-Test

## References

### 2019a

- (Laerd Statistics, 2019) ⇒ Laerd Statistics (2019). "One-way ANCOVA in SPSS Statistics". Retrieved: 2019-04-12.
- QUOTE: The one-way ANCOVA (analysis of covariance) can be thought of as an extension of the one-way ANOVA to incorporate a covariate. Like the one-way ANOVA, the one-way ANCOVA is used to determine whether there are any significant differences between two or more independent (unrelated) groups on a dependent variable. However, whereas the ANOVA looks for differences in the group means, the ANCOVA looks for differences in adjusted means (i.e., adjusted for the covariate). As such, compared to the one-way ANOVA, the one-way ANCOVA has the additional benefit of allowing you to "statistically control" for a third variable (sometimes known as a "confounding variable"), which you believe will affect your results. This third variable that could be confounding your results is called the covariate and you include it in your one-way ANCOVA analysis.

### 2019b

- (Horn, 2019) ⇒ Robert A. Horn (2019). "Umderstanding Aanalysis of Covariance". "Educational Psychology 625: Intermediate Statistics" Course Handout. Copyright: 2008 Northern Arizona University. Published Online: 2008. Retrieved: 2019-04-12.
- QUOTE: A
**one-way analysis of covariance (ANCOVA)**evaluates whether population means on the dependent variable are the same across levels of a factor (independent variable), adjusting for differences on the covariate, or more simply stated, whether the adjusted group means differ significantly from each other. With a one-way analysis of covariance, each individual or case must have scores on three variables: a factor or independent variable, a covariate, and a dependent variable. The factor divides individuals into two or more groups or levels, while the covariate and the dependent variable differentiate individuals on quantitative dimensions. The one-way ANCOVA is used to analyze data from several types of studies; including studies with a pretest and random assignment of subjects to factor levels, studies with a pretest and assignment to factor levels based on the pretest, studies with a pretest, matching based on the pretest, and random assignment to factor levels, and studies with potential confounding (Green & Salkind, 2003).

- QUOTE: A

### 2012

- http://www.vassarstats.net/vsancova.html
- One-Way ANCOVA for Independent Samples. These units will perform an analysis of covariance for k independent samples, where the individual samples, A, B, etc., represent k quantitative or categorical levels of the independent variable; DV = the dependent variable of interest; and CV = the concomitant variable whose effects one wishes to bring under statistical control. The units in this first batch require the direct entry of data, item by item, and as they open you will be prompted to enter the size of the largest of your several samples.
.... For k>4, there is a downloadable Excel spreadsheet available.

- One-Way ANCOVA for Independent Samples. These units will perform an analysis of covariance for k independent samples, where the individual samples, A, B, etc., represent k quantitative or categorical levels of the independent variable; DV = the dependent variable of interest; and CV = the concomitant variable whose effects one wishes to bring under statistical control. The units in this first batch require the direct entry of data, item by item, and as they open you will be prompted to enter the size of the largest of your several samples.