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Combining data from two Trials

Abbiegraham

Hi,

Please could I get advice to analyse the following dataset. In a trial, animals were provided with feed in different forms (round vs square) and concentrations (100, 80, 60%). This was trialled twice, (Trial 1 and Trial 2- everything was kept similar between both trials). The animals are kept in pens, so each performance parameter (bodyweight etc. is measured as a pen average).

I want to combine the results from Trial 1 and 2 and to determine the effects of:

Trial

Feed form

Feed Concentration

Treatment

Age

Pen

Please can someone advise if Pen and Trial should be considered as random effects? It is the three effects which I have highlighted that I am most interested in. I have tried running the analysis but my outputs so far do not make much sense so any help would be appreciated- I have JMP, not JMP Pro.

@Phil_Kay

Thanks

Abbie

Trials combined JMP.xlsx

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All comments

Abbiegraham

Apologies- the wrong file was attached. Please use this one instead.

Many Thanks,

Abbie

Trials combined JMP.xlsx

Dan_Obermiller

Before providing my opinion to your question, a few things that I noticed on a very quick look at your data.

First, get your data into JMP! Excel files are nice, but JMP files are better, especially when it comes to analysis!

I noticed that you have more than 2 forms of feed. You also have PRILL and POWDER. These look like "add-on" types of trials, meaning they were not part of the original design. I will assume that you will remove these rows from the table as there is not much data on those forms anyhow.

Once prill and powder have been removed, your treatment column is not necessary. It is a combination of Concentration and Form. Therefore, just using Concentration and Form makes the treatment redundant and not needed.

A random effect is an effect where the choice of level is chosen randomly from a larger set. It seems to me that Pen would be random. You have a large selection of pens and the ones used for these trials are randomly chosen.

Trial also sounds like a random effect to me. You could certainly do more trails, so the two that you did run are a "selection" from a larger set.

You state that your analysis did not make sense. The community will be much more equipped to help you if you provide the JMP file with your analyses and with more specific questions on what does not make sense to you.

statman

Echoing Dan, why aren't you attaching the JMP file? In your excel file, there are a number of columns that have not been defined by your brief description. You should define each column (and if it is an x or a y). For each response variable(s) you will need to provide how much of a change in the metric matters from a scientific perspective (practical significance).

After that, we'd be happy to take a look.

Abbiegraham

Thanks @statman @DanP

I have attached the JMP File- and made the changes suggested.

I have ran a mixed model with Trial and Pen as random effects, then Form, Concentration, Age, Form x Age and Concentration x Age on the data. Every other parameter (uniformity, FCR etc.) is a response variable.

I have ran this on the bodyweight data and the analysis makes sense to me now. Would I be correct in interpreting that for bodyweight:

There were significant effects of everything apart from Age x Form. Out of the two random effects, "pen" had a significant effect, but "Trial" did not.

Is my analysis correct, and is this the correct approach to take, rather than a repeated measures analysis? Is there any further analysis you would recommend?

Thank you

Abbie

JMP FILE 2 Trials combined.jmp