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 Answer 1


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?

  • when we have a continuous outcome variable
  • when data are clustered (for example, repeated observation on participants or students within classes)
  • when we have sufficient number of clusters to enable estimation of the random effect (variance)
  • when we are not interested in the "effects" of the clusters themselves.

Additionally, ANOVA cannot be used (though there may be a work-around), and mixed models offer a much better alternative, when

  • we have missing data, or
  • the experimental design is unbalanced, or
  • we have multiple (cross-classified or nested) random effects, or
  • we would like to allow the effect of covariates to differ among each level of a grouping variable (random coefficients or random slopes), or
  • when we have an outcome variable that can't be plausibly considered as continous (such as count data and nominal data) - in which case we would use a generalised linear mixed model.

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.

  • $\begingroup$ That helps clarify my question. In my case i am examining the influence of one independent var with 2 levels, onto two dependent var. Do you advise me to use linear mixed methods or MANOVA. It is a within subject test design whereby the same subjects were exposed to the two stimuli (2 llevels of the independent var). kindly advise $\endgroup$
    – user39531
    Sep 10, 2016 at 16:07
  • $\begingroup$ @user39531 it is difficult to say without more information. Please ask a new question with the mixed-model and anova tags, giving as much detail as possible about your experimental design. $\endgroup$ Sep 10, 2016 at 22:08
  • $\begingroup$ I posted a new question under "Which type of Analysis." Thanks $\endgroup$
    – user39531
    Sep 11, 2016 at 1:21
  • $\begingroup$ Just curious how do we do a bar graph to compare the Means of the dependent var in SPSS. I tried graph>legacy>bar> clustered etc, but could not figure out. I have for example the following dependent var: PQ_High and PQ_Low; and ATT_High and ATT_low (as scale interval data). I want to compare the low and high mean of PQ and of ATT as a bar graph. Please advise $\endgroup$
    – user39531
    Sep 11, 2016 at 3:26
  • $\begingroup$ @user39531 questions about how to use software are off-topic here. You could try asking on stackoverflow. $\endgroup$ Sep 11, 2016 at 8:22

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