[R] Modelling categorical variables

PIKAL Petr
Tue, 08 Sep 2015 12:25:19 -0000

Hi

You probably wont get many answers because:

1 -you post in HTML (post in plain text)
2 -you provide data which are unreadable (copy output of dput(yourdata) instead)
3 -you ask statistical question which are rarely answered here (they are better
suited to stackexchange list)

Regarding your models nothing prevents you to test any of them - lm, glm, ...
Or go through some available documents on CRAN like e.g.

Using R for Data Analysis and Graphics - Introduction, Examples and Commentary?
by John Maindonald (PDF, data sets and scripts are available at JM's
homepage).
?Practical Regression and Anova using R? by Julian Faraway (PDF, data sets and
scripts are available at the book homepage).

among many others to learn how to use R for modelling.

Cheers
Petr


> -----Original Message-----
> From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Jessica
> Lavabre
> Sent: Tuesday, September 08, 2015 11:01 AM
> To: r-help at r-project.org
> Subject: [R] Modelling categorical variables
>
> Hi,
>
> I am a beginner with statistics and R and have no clue on how to model
> my data. I have collected information on seed traps (ID) that includes
> the habitat type (Hab) and different measures of distances. Also I have
> applied a modularity analysis, so that the seeds traps are grouped into
> modules. My dataset is as follow:
>
>
>
> *ID    Hab  Module    DistEdge    MeanDist1    MeanDist2    MeanDist3
> F48    F       A         21.768       24.941          6.033
> 27.642    F50    F       E         35.666**       60.505
> 149.927 *
> *       48.582   F52    F       B**         12.243**       103.041
> 72.908  *
> *        102.375    N02    N      B **        58.681**
> 129.59          127.344   *
> *     131.383   N17    N      B**         62.829**       72.827 **
> 76.736  *
> *        77.644  N22    N      B**         89.207**       78.719  **
> 75.005   *
> *       81.176N33    N      A**         23.288**       35.48    **
> 25.317 *
> *         36.931    N40    N      B**         36.734**       62.234 **
> 30.68   *
> *         61.885    N47    N      E  **       60.443**       66.367  **
> 150.892 **       55.097   *
>
> I am looking for a way to analyze if there is any correlation between
> the Module classification and the other variables. My difficulties here
> are:
> 1 - is there a way to model my data where Module is the response
> variable (something like Module~Hab*DistEdge*MeanDist1) ? If so, which
> model should I use (I only have a bit of experience with glm) and which
> distribution?
> 2 - Is that a problem if I have different types of predictor variable
> (factor and numerical)?
>
> Any help would be greatly appreciated,
>
> -- Jessica Lavabre-Micas
>
>       [[alternative HTML version deleted]]
>
> ______________________________________________
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> PLEASE do read the posting guide http://www.R-project.org/posting-
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> and provide commented, minimal, self-contained, reproducible code.

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