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#### furanosa2000

Dear all,

I have a set of data of an experiment. In the experiment I have 3 factors and made 3 repetition, and on each repetition I took 10 measurement. Lets say the factors are A, B and C. I made 3 repetition which means I will have experiment A1, A2, A3, B1, B2, B3, C1, C2, C3. On each repetition, I took 11 measurement to the same unit experiment, which gave me A1a, A1b, ..., A1j etc.

I want to analyze using one way ANOVA whether there is differences between the factors. At first, I take means of each repetition and consider that as a single value and analyze it directly using one way ANOVA (so I only have 9 data). But then, I realize that each repetition has its own variability, which may affect the final decision whether the factors giving different effect. So I tried to analyze the data again, but this time using GLM and considered the 11 measurement nested within the repetition (giving total data to analyze of 198). I used the following model for the GLM: factor repetition(factor)

The ANOVA result of GLM is totally different from the one way ANOVA. When I used one way ANOVA the p value is 0.07, while when using the GLM model, the p value is <0.00. Does anyone have any idea whether we can consider several measurements as nested in the replicate?

For information I attach the data.

I have a set of data of an experiment. In the experiment I have 3 factors and made 3 repetition, and on each repetition I took 10 measurement. Lets say the factors are A, B and C. I made 3 repetition which means I will have experiment A1, A2, A3, B1, B2, B3, C1, C2, C3. On each repetition, I took 11 measurement to the same unit experiment, which gave me A1a, A1b, ..., A1j etc.

I want to analyze using one way ANOVA whether there is differences between the factors. At first, I take means of each repetition and consider that as a single value and analyze it directly using one way ANOVA (so I only have 9 data). But then, I realize that each repetition has its own variability, which may affect the final decision whether the factors giving different effect. So I tried to analyze the data again, but this time using GLM and considered the 11 measurement nested within the repetition (giving total data to analyze of 198). I used the following model for the GLM: factor repetition(factor)

The ANOVA result of GLM is totally different from the one way ANOVA. When I used one way ANOVA the p value is 0.07, while when using the GLM model, the p value is <0.00. Does anyone have any idea whether we can consider several measurements as nested in the replicate?

For information I attach the data.