Anova random effects

I have a question about the way to code nested factor in the data. Should each level be identified with a unique code (I think this is required for lmer) or each factor should be repeated. Example:
3 treatments (enrichment), repeated 3 times (different places, uniques):
enrichment place place_unique
A 1 1
A 2 2
A 3 3
B 1 4
B 2 5
B 3 6

I really enjoyed your threads and am amazed with the way you explain things that is understandable even to a beginner like me. Came across your website by accident while looking for chi-square vs logistic regression explanations. Thank you! A quick question: The place where I work is currently using a tool to categorize feeding difficulties in children and it has never been validated. BUT it has been widely used world wide (~8 countries) with studies proving its efficacy. Is it feasible to make a research using this tool without going through a validation study? Thanks very much !

Kempthorne uses the randomization-distribution and the assumption of unit treatment additivity to produce a derived linear model , very similar to the textbook model discussed previously. [30] The test statistics of this derived linear model are closely approximated by the test statistics of an appropriate normal linear model, according to approximation theorems and simulation studies. [31] However, there are differences. For example, the randomization-based analysis results in a small but (strictly) negative correlation between the observations. [32] [33] In the randomization-based analysis, there is no assumption of a normal distribution and certainly no assumption of independence . On the contrary, the observations are dependent !

Anova random effects

anova random effects


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