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thrillhouse86
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I am having a lot of trouble conceptually understanding the idea of a random effect in ANOVA testing - more specifically identifying whether a factor is random or fixed
Thanks,
Thrillhouse86
Thanks,
Thrillhouse86
Random effects in ANOVA refer to factors that are selected randomly from a larger population, while fixed effects refer to factors that are specifically chosen by the researcher to be included in the study. Random effects are typically used to account for variability within a population, while fixed effects are used to test specific hypotheses.
The decision to use random or fixed effects in ANOVA depends on the research question and the design of the study. Random effects are more appropriate when the goal is to generalize the results to a larger population, while fixed effects are more suitable for testing specific hypotheses.
Yes, it is possible to include both random and fixed effects in the same ANOVA model. This is known as a mixed effects ANOVA and is commonly used in research studies with complex designs or multiple factors.
Examples of random effects in ANOVA include gender, age, and geographic location, as these factors are typically selected randomly from a larger population. Fixed effects in ANOVA may include experimental conditions, treatment groups, or specific variables that the researcher wants to test.
Random effects can increase the generalizability of the results, as they account for variability within a larger population. On the other hand, fixed effects can provide more specific and focused information about the factors being tested. The inclusion of both random and fixed effects can provide a more comprehensive understanding of the data in an ANOVA analysis.