Three-Way ANOVA
The three-way ANOVA is used by statisticians to determine whether there is a three-way relationship among variables on an outcome. The three-way ANOVA is used by statisticians to determine whether there is a three-way relationship among variables on an outcome. A pharmaceutical company, for example, may do a three-way ANOVA to determine the effect of a drug on a medical condition. For example, a pharmaceutical company may do a three-way ANOVA to test a drug, given the different genders or ethnicities of their subjects. A three-way ANOVA tests which of three separate variables have an effect on an outcome, and the relationship between the three variables.
What Is the Three-Way ANOVA?
The three-way ANOVA is used by statisticians to determine whether there is a three-way relationship among variables on an outcome. It determines what effect, if any, three factors had on an outcome. Three-way ANOVAs are useful for gaining an understanding of complex interactions where more than one variable may influence the result and have many applications in finance, social science, and medical research, among a host of other fields.
A three-way ANOVA is also known as three-factor ANOVA. By using ANOVA, a researcher is able to determine whether the variability of the outcomes is due to chance or to the factors in the analysis.
Understanding a Three-Way ANOVA
A pharmaceutical company, for example, may do a three-way ANOVA to determine the effect of a drug on a medical condition. One factor would be the drug, another may be the gender of the subject, and another may be the ethnicity of the subject.
These three factors may each have a distinguishable effect on the outcome. They may also interact with each other. The drug may have a positive effect on male subjects, for example, but it may not work on males of a certain ethnicity. Three-way ANOVA allows the scientist to quantify the effects of each and whether the factors interact.
Related terms:
Adjusted Mean
The adjusted mean accounts for outlines and anomalies in a data set, thereby offering a more accurate mean average. read more
Analysis Of Variances (ANOVA)
Analysis of variances (ANOVA) is a statistical examination of the differences between all of the variables used in an experiment. read more
Chi-Square (χ2) Statistic
A chi-square (χ2) statistic is a test that measures how expectations compare to actual observed data (or model results). read more
Spurious Correlation
In statistics, a spurious correlation, or spuriousness, refers to a connection between two variables that appears causal but is not. read more
Statistics
Statistics is the collection, description, analysis, and inference of conclusions from quantitative data. read more
Two-Way ANOVA
A two-way ANOVA test is a statistical test used to determine the effect of two nominal predictor variables on a continuous outcome variable. read more