[R-sig-eco] help

[Thierry Onkelinx]

Dear Baoping,

You could standardize the weight by stage. That would remove the
confounding between weight and stage.

Best regards,

ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium

To call in the statistician after the experiment is done may be no more
than asking him to perform a post-mortem examination: he may be able to say
what the experiment died of. ~ Sir Ronald Aylmer Fisher
The plural of anecdote is not data. ~ Roger Brinner
The combination of some data and an aching desire for an answer does not
ensure that a reasonable answer can be extracted from a given body of data.
~ John Tukey

2016-05-19 2:39 GMT+02:00 lbp at njau.edu.cn <lbp at njau.edu.cn>:

> Now I have difficulty to choose between two modelling approach. Here is th
> story. To examine the clutch size laid by a parasitic wasp into caterpillar
> hosts which varies in age and size, we exposed individual larvae of  three
> stages, after individually weighed, to parasitism, and the number of wasps
> emerged from each host (brood size) was recorded. Because host size and
> stage are mutually counfounding factors, the older the bigger, I have two
> modelling choices to separate the effect of stage and size. One is to make
> separate analyses, first analyzing the effct of stages in a model without
> the variable size, and then analyze the effect of the size under each stgae
> (several models); another approach is to make one analysis, put stage and
> size together in the same model to evaluate their separate and interacted
> effects on brood size.  For the later approach, the variable size actualy
> contains the inflormation about the stage, thus violating the independence
> assumation. I am won!
>  dering which appraoch is approriate.
>
>    Thanks for any help.
>
>   Baoping
>
>
>
>
> E-mail: lbp at njau.edu.cn
> Phone: 86 (25) 84396394
>
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