_edited_ed.png)
Mixed ANOVA (Analysis of Variance) is a statistical analysis technique used to test the differences in means across groups that have multiple factors, which include both repeated measures and independent groups. Mixed ANOVA is suitable for analyzing data collected from distinct sample groups with measurements taken multiple times under different conditions or over different periods.
When to Use Mixed ANOVA?
Mixed ANOVA is used in situations where the impact of several factors with different characteristics is studied, and comparisons of results across groups with repeated measures over time are required. Examples include:
Studying the impact of treatments (new treatment vs. traditional treatment) and time (before and after treatment) on patients' stress levels.
Analyzing the effect of training types (group training vs. individual training) and time (before and after training) on employees' performance.
Example Research Hypotheses Suitable for Mixed ANOVA
Example Hypothesis 1:
Studying the impact of learning methods (online vs. classroom) and time (before and after the test) on students' learning outcomes:
Hypothesis 1 (Main Effect of Learning Method): Learning methods have an effect on students' learning outcomes.
Hypothesis 2 (Main Effect of Time): Time has an effect on students' learning outcomes.
Hypothesis 3 (Interaction Effect): There is an interaction effect between learning methods and time on students' learning outcomes.
Example Hypothesis 2:
Studying the impact of exercise programs (Program A vs. Program B) and time (before and after exercise) on muscle strength levels:
Hypothesis 1 (Main Effect of Exercise Program): Exercise programs have an effect on muscle strength levels.
Hypothesis 2 (Main Effect of Time): Time has an effect on muscle strength levels.
Hypothesis 3 (Interaction Effect): There is an interaction effect between exercise programs and time on muscle strength levels.
Example Hypothesis 3:
Studying the impact of therapy methods (group therapy vs. individual therapy) and time (before and after therapy) on patients' stress levels:
Hypothesis 1 (Main Effect of Therapy Method): Therapy methods have an effect on patients' stress levels.
Hypothesis 2 (Main Effect of Time): Time has an effect on patients' stress levels.
Hypothesis 3 (Interaction Effect): There is an interaction effect between therapy methods and time on patients' stress levels.
Characteristics of Factors Suitable for Mixed ANOVA
Dependent Variable: Must be a quantitative variable that can be measured, such as performance scores, stress levels, or satisfaction levels.
Independent Variables: Consist of two types:
Repeated Measures: Variables that are measured multiple times under different conditions or over different periods, such as time before and after training.
Independent Groups: Variables that divide the sample groups into distinct groups, such as types of training.
Interpreting Mixed ANOVA Results
Interpreting Mixed ANOVA results involves examining both main effects and interaction effects as follows:
Main Effects:
Check the p-value for each independent variable. If the p-value is less than 0.05, it indicates that the variable has a significant effect on the dependent variable.
Consider the F-value to determine the importance and magnitude of the effect.
Interaction Effects:
Check the p-value for the interaction effect. If the p-value is less than 0.05, it indicates that there is a significant interaction effect between the two independent variables.
Analyze Interaction Plots to help interpret the nature of the interaction effect, such as whether the effects are synergistic or antagonistic.
Mixed ANOVA is a valuable tool for analyzing the effects of multiple factors with repeated measures and distinct sample groups. Using Mixed ANOVA helps us understand the complexity of how different factors influence the dependent variable. Interpreting the results of the analysis allows us to make effective decisions that are consistent with the actual data.
At Data Investigator, we have a team of experts who can assist with data analysis using Mixed ANOVA and other statistical tools to ensure you receive high-quality data that can be used to develop your business. Contact us for comprehensive and reliable data analysis services.
For more information, please kindly contact:
E-mail: info@datainvestigatorth.com
Line: @datainvestigator
Call: 063-969-7944
Comments