Can anyone suggest to me on how i can develop a model in R to compare how two species of mosquitoes are affected by habitat characteristics using cbind function? Among other variables i suspect distance from the open lake may play a role in their abundance and distribution in this area.
Simplified: The cbind() function in R, takes two vectors and bind them together, such that each vector becomes the column of the resulting matrix. E.g.:
v1 = c(1,2,3,4,5)
v2 = c(6,7,8,9,10)
cbind(v1,v2)
v1 v2
[1,] 1 6
[2,] 2 7
[3,] 3 8
[4,] 4 9
[5,] 5 10
Hope this helps regarding cbind(). Regarding the second half, I suggest you google the lm() function in R and in more general terms, google and take a closer look at linear modelling. I agree that the distance to open fresh water plays a role as a variable. However remember, that mosquitos can hatch in even small quantities of water, e.g. a puddle
/L
Dear Leon,
Thank you for the contribution. Clearly, that's what cbind does, unfortunately, we need to know how it can be applied to compare differences or how it affects the two species, with respect to distance + other variables. Also, notice that this is lake situation where there are no puddles. A dataset with columns which i need to use the above to merge. Appreciated,
The cbind() function is used for constructing matrices, it has nothing to do with the actual data analysis. As I understand your question you want to compare how distance-to-nearest-lake and alike variables impacts mosquito abundance? In that case and as previously suggested, you should look in to linear modelling using the lm() function. In case you have two datasets you need to merge, then you should look into the merge() function. Remember you can ask R for help simply by typing ?lm or ?merge at the prompt.
Leon,
Maybe my question is unclear. At the littoral shore I sampled points from the lake-edge to towards open lake, then got two dominant species. One habitat type, which thy seem to like and dominant for both in the model astonish me.... But, I presuppose distance from the open lake to the lake edge could be another factor, that can impact on lake stability and influence the two species distribution. My second hypothesis therefore is that the two-dimensional mean-vector of the two species are the same . Zuur et al. tells me cbind function can help me account for the differences between the two species, but again the limitation is how to arrive at these differences (using cbind function). I believe cbind goes beyond matrices and could be the right statistical procedure to sniff this stuff out. What's your opinion,
Gabriel,
Please start an R-session and type the following: ?cbind then you will arrive at this help: https://stat.ethz.ch/R-manual/R-devel/library/base/html/cbind.html which tells you that: "Take a sequence of vector, matrix or data-frame arguments and combine by columns or rows, respectively"
Therefore once again the cbind() function is NOT a statistical test!
I suggest you google something along the lines of 'linear modelling in r'
Hi Gabriel,
I think what you are looking for is a MANOVA (multivariate anova), which allows you to test the response of multiple response variables to a set of predictors. The first step in this analysis is to combine your response variable vectors (species in your case) into a matrix using the cbind() function, and this matrix then becomes your 'response variable'. e.g.
Y
As said above, I understand cbind is superuseful to put a response variable composed of two items, for example the actual response of interest (e.g. counts) and some sort of control over it (e.g. observation effort in time). What I don't quite understand is how the two items are managed by the actual test (e.g. Manova or regression model). I'd appreciate if anyone can add more info on this. Cheers.
Found a great explanation here:
http://rcompanion.org/handbook/J_02.html
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