What is ANCOVA vs ANOVA?

ANOVA is a process of examining the difference among the means of multiple groups of data for homogeneity. ANCOVA is a technique that remove the impact of one or more metric-scaled undesirable variable from dependent variable before undertaking research.

What does ANCOVA stand for in statistics?

Analysis of covariance (ACOVA) incorporates one or more regression variables into an analysis of variance.

How do you interpret ANCOVA?

If the p-value is LESS THAN . 05, then there was a statistically significant difference between the groups or levels of the variable. If the p-value is MORE THAN . 05, then there was NOT a statistically significant difference between the groups or levels of the variable.

What are the benefits of ANCOVA?

Advantages of ANCOVA include better power, improved ability to detect and estimate interactions, and the availability of extensions to deal with measurement error in the covariates. Forms of ANCOVA are advocated that relax the standard assumption of linearity between the outcome and covariates.

What are the assumptions of ANCOVA?

ANCOVA has the same assumptions as any linear model (see your handout on bias) except that there are two important additional considerations: (1) independence of the covariate and treatment effect, and (2) homogeneity of regression slopes.

What is a covariate in ANOVA?

Covariates are usually used in ANOVA and DOE. In these models, a covariate is any continuous variable, which is usually not controlled during data collection. Including covariates the model allows you to include and adjust for input variables that were measured but not randomized or controlled in the experiment.

What are the disadvantages of ANCOVA?

The main disadvantage of ANCOVA is the underlying assumption of no difference across groups or treatment arms in terms of the covariate used in the analysis and the homogeneity of regression slopes.

What is ANCOVA in SPSS?

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.

When should I run ANCOVA?

ANCOVA is a type of general linear model (GLM) that includes at least one continuous and one categorical independent variable. ANCOVA is useful when the effect of experimental conditions is important while there is an additional continuous variable in the study.

Where is ANCOVA used?

Equating Non-Equivalent Groups: Another, though controversial, use of ANCOVA is to correct for initial group differences that exists on the dependent variable. Using this method, the researcher adjusts means on the dependent variable in an effort to correct for individual differences.

What assumption does ANCOVA?

In addition, ANCOVA requires the following additional assumptions: For each level of the independent variable, there is a linear relationship between the dependent variable and the covariate. The lines expressing these linear relationships are all parallel (homogeneity of regression slopes)