statistics - Partially nested/blocked experimental design in R -

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There are 10 participants in the design of the experiment to get them all to go through A, B, C, D for treatment. However, going through 1-5 conditions for participants, E, F and participants, through 6-10 conditions, H

I am using the NLM package to deal with longer data I stop the list-wise extinction of participants. Measured variable = dv, fixed effect = position, random effect = participant). When everything is just crossed, then I have it: 

  lme (DV ~ cond, random = ~ 1 | ppt, data = outputdata, method = "ml", na.action = What are the prescribed figures for the first part (conditions A, B, C, D), while the second part E, F and G, H are nested ... Any help or guidance will be appreciated! Thanks. /p>  
 
 
 I think your design can be considered as a planned "missing" design, where a part of the subjectThey are not in contact with some conditions in the planned manner (see Enders, 2010). If these values ​​are "completely lost completely" then you can treat your data as a condition with the absent values ​​according to conditions -Referred repetitive measures can be obtained from the design.  
 I recommend that you get a variable "block" from other topics, going through the subjects of AD Plus E and F. After this you can refer your model to  
  summary (M1 and LT; - LME (DV ~ cond, random = ~ 1 | block / PPT, data = outcome, data, method = "REML" ) / Code>  
 If you make topics randomly random in 2 blocks, there should not be significant variability related to blocks. You can test it by fitting any other model without blocking random effects and thus compare 2 models:  
  summary (m0 <- lme (DV ~ cond) , Random = ~ 1 | ppt, data = outadata data, method = "REML")) ANOVA (M, M1)  
 
  method = "REML"  Because we are comparing the nested model which is different in random effect To predict definite effects, you can replenish the model with a better fit than the  method = "ml"  (hopefully M.). 
 
 If you have not collected data yet, then I strongly encourage you to randomly allocate topics for 2 blocks. To block 1 from topic 1-5 (i.e., the conditions are going through E and F) and variables in the other blocks to rotate the subjects of 6-10 (for example, those using for the process Time, technician) can start.

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