Test Batteries in Animal Models of Psychopathology
The ANOVA test is an abbreviation for analysis of variance and these tests specialize in studies with three or more groups and contain two or more independent variables. Additionally, the ANOVA tests are preferable compared to the t-test, because the ANOVA prevents the risk of type 1 error due to the use of multiple groups. There are three types of ANOVA test and they are one-way ANOVA, one-way repeated-measures, and two-way ANOVA (Corty, 2016).
One-way ANOVA: Between-subjects vs. Within-subjects
One-way ANOVA compares the means of three or more groups to examine if they are different from one another or if they are the same. There are two types of one-way ANOVA test and they are between-subjects and within-subjects. One-way between-subject ANOVA depicts a test where the compared groups are not related in any way and the participants are independent from one another. Additionally, this type of tests is based on the different treatments that the different groups receives. For example, a researcher has three groups that were randomly selected where age, sex, and weight are completely different. Group one smoked one cigarette, group two smoked half pack of cigarettes, and group three smoked one pack of cigarettes. This difference in cigarettes smoked shows that each group had different treatments and did not experience the same effects because of age, sex, and weight.
Whereas, within-subjects means the participants are related in some way, therefore, the groups received the same treatment but different individual effects. For example, group one, group two, and group three smoked half pack of cigarettes, but the effect on the individuals will be different due to height, weight, age, sex, if they ate before the test, and nicotine tolerance (Corty, 2016).
One-way repeated-measures ANOVA
One-way repeated-measures ANOVA compares the means of three or more dependent samples and examines if the means are different or the same when the participants are the same in each group. This test is used to measure studies with the same cases measure under multiple conditions, and the same cases measured at multiple points of time. For example, examining alcohol tolerance of college students over a period of time, such as a group of freshmen compared to the same set of participants over the next four years of college (freshmen, sophomore, junior, and senior) (Corty, 2016).
Two-way ANOVA examines the effect of two independent variables on a dependent variable but in simple terms. This test consists of two factors, the main effects, which analyze the overall impact of the independent variable and there is interaction effect, which is the effect that one factor (independent variable) has on the other factor. This test is preferable when there is one measurement, such as a quantitative variable with two nominal variables, such as gender. For example, studying the interaction between gender and education level in relation to annual income. The gender (male-1 and female-2) and educational level (high school-1, BS/BA-2, and Masters/PHD-3) are the independent categories and the dependent is the annual income (Corty, 2016).
Corty, E. (2016). Using and interpreting statistics: A practical text for the behavioral, social, and health sciences (3rd ed.). New York, NY: Macmillan Learning.
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