Cross Validated Asked by user39531 on November 24, 2021
1) What is the difference between conducting a Linear Mixed Models and an ANOVA?
2) In which circumstances do we conduct a Linear Mixed Models Analysis?
1) What is the difference between conducting a Linear Mixed Models and an ANOVA?
ANOVA models have the feature of at least one continuous outcome variable and one of more categorical covariates. Linear mixed models are a family of models that also have a continous outcome variable, one or more random effects and one or more fixed effects (hence the name mixed effects model or just mixed model).
There are sub-classes of ANOVA models that allow for repeated measures, a mixed ANOVA which has one within-subjects (categorical) covariate and at least one between-subjects (categorical) covariate, and repeated measures ANOVA which has at least two within-subjects (categorical) covariate and at least one between-subjects (categorical) covariate.
2) In which circumstances do we conduct a Linear Mixed Models Analysis?
Additionally, ANOVA cannot be used (though there may be a work-around), and mixed models offer a much better alternative, when
3) How do we obtain such a graph using the above model (Mixed Model or ANOVA) in SPSS to compare the "Low" and "High" condition of the product?
The figure appears to be a simple plot of means for 4 groups. Since it appears to be purely descriptive it isn't therefore something to be obtained from a model.
It appears to be typical of the type of data analysed with a two-way ANOVA - that is, a model with a continuous outcome variable, and two categorical covariates.
Answered by Robert Long on November 24, 2021
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