CODEWITHSUNDEEP
ranovamixed-models
PeterPer
PeterPer

Reputation: 55

Repeated Measures: From SPSS to R

I am looking to run a mixed effects model in R based on how I used to run the stats in SPSS with a repeated measures ANOVA. Here is how I set up the repeated measures ANOVA in SPSS. How would I convert this to lme4 in R?

Key: EBT100... is the name of the task, Genotype is my IV, and my within-subject factors are Day (5 levels) and Cue (9 levels). Att is my DV.

In R, this is the code that I am trying to run: In R, here is my code:

lmeModel <- lmer(Att ~ Genotype*Day*Cue + (1|Subject)

My Genotype Effect is the same between R and SPSS (p~0.12), but all of my interactions are different (Genotype x Day, Genotype x Cue, Genotype x Day x Cue).

R (lme4) Output:

                 Sum Sq Mean Sq NumDF DenDF F.value    Pr(>F)    
Genotype            488   243.9     2    32   2.272   0.11954    
Day               25922  6480.4     4  1408  60.356 < 2.2e-16 ***
Cue               35821  4477.6     8  1408  41.703 < 2.2e-16 ***
Genotype:Day       3646   455.7     8  1408   4.244 4.751e-05 ***
Genotype:Cue        736    46.0    16  1408   0.429   0.97560    
Day:Cue            5063   158.2    32  1408   1.474   0.04352 *  
Genotype:Day:Cue   3297    51.5    64  1408   0.480   0.99984

SPSS Repeated Measures ANOVA output:

                   F.value   Pr(>F)    
Genotype            2.272    0.120    
Day                 9.603    0.000
Cue                 83.916   0.000
Genotype:Day        0.675    0.712
Genotype:Cue        0.863    0.613    
Day:Cue             3.168    0.00  
Genotype:Day:Cue    1.031    0.411

You can see that the main effect of Genotype is the same for both R and SPSS. Additionally, in R, my DenDF output is not correct either. Any idea as to why this would be?

Even more... Using ezANOVA, with the same dataset that I am using for lme4, this is my code:

anova <- ezANOVA(data = dat,
    wid = Subject,
    dv = Att,
    within = .(Day, Cue),
    between = Genotype,
    type = 3)

ezANOVA Output:

            Effect DFn  DFd          F            p p<.05         ges
2         Genotype   2   32  2.2715034 1.195449e-01       0.044348362
3              Day   4  128  9.6034152 8.003233e-07     * 0.103474748
5              Cue   8  256 83.9162989 3.938364e-67     * 0.137556761
4     Genotype:Day   8  128  0.6753544 7.124675e-01       0.015974029
6     Genotype:Cue  16  256  0.8624463 6.133218e-01       0.003267726
7          Day:Cue  32 1024  3.1679308 1.257738e-08     * 0.022046134
8 Genotype:Day:Cue  64 1024  1.0313631 4.115000e-01       0.014466102

How can I convert ezANOVA to lme4?

Any information would be greatly appreciated! Thank you!

Upvotes: 0

Views: 559

Answers (1)

Maurits Evers
Maurits Evers

Reputation: 50668

First off: It would be very beneficial and instructive if you could share your data, which allows for an easier comparison of lmer results with those from SPSS/ezANOVA.

Personally I prefer mixed effect (i.e. hierarchical) models as I find them easier to understand (and construct), so I am not that familiar with repeated measure ANOVA. Translating the latter into the former boils down to correctly translating within/between effects of your RM-ANOVA into the appropriate terms of your lmer mixed-effect model.

Provided I understood you correctly, the following seems consistent with your model problem statement:

  1. Genotype is your fixed effect
  2. Subject is your random (grouping or blocking) effect
  3. Day is a within-Subject effect
  4. Cue is a within-Subject effect

The corresponding lmer model should look something like this:

lmer(Obs ~ Genotype * Day * Cue + (Day:Cue|Subject)

If this is not tractable, you should try

lmer(Obs ~ Genotype * Day * Cue + (Day|Subject) + (Cue|Subject) + (1|Subject)

Upvotes: 1

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