The repeated-measures ANOVA is a two-stage process. Which of the following accurately describes what happens during this process?
A repeated-measures ANOVA has SSwithin treatments = 26 and SSbetween subjects = 12. For this analysis, what is the value for SSerror?
A two-factor study with two levels of factor A and three levels of factor B uses a separate group of n = 5 participants in each treatment condition. How many participants are needed for the entire study?
In a repeated-measures ANOVA, the variability within treatments is divided into two components. What are they?
A two-factor research study is used to evaluate the effectiveness of a new blood-pressure medication. In this two-factor study, Factor A is medication versus no medication and factor B is male versus female. The medicine is expected to reduce blood pressure for both males and females, but it is expected to have a much greater effect for males. What pattern of results should be obtained if the medication works as predicted?
The results of a two-factor analysis of variance produce df = 1, 30 for the F-ratio for factor A, and df = 2, 30 for the F-ratio for the AxB interaction. Based on this information, how many levels of factor B were compared in the study?
A researcher reports an F-ratio with df = 2, 40 from a repeated-measures ANOVA. How many treatment conditions were compared in this experiment?
How many separate groups of participants would be needed for an independent-measures, two-factor study with 3 levels of factor A and 4 levels of factor B?
The results from a two-factor analysis of variance show a significant main effect for factor A and a significant main effect for factor B. Based on this information, what can you conclude about the interaction?
A two-factor analysis of variance produces an F-ratio for factor A that has df = 3, 36. This analysis is comparing three different levels of factor A.
For an independent-measures two-factor analysis of variance, all F-ratios use the same denominator.
A repeated-measures study uses a sample of n = 8 participants to evaluate the meandifferences between two treatment conditions. The analysis of variance for this study will have dferror = 7.
Because the repeated-measures ANOVA removes variance caused by individual differences, it usually is more likely to detect a treatment effect than the independent-measures ANOVA is. Obtaining a significant interaction means that both factors A and B have significant main effects.
A repeated-measures study uses a sample of n = 10 participants to evaluate the mean differences among three treatment conditions. For this study, dfbetween subjects = 18.