Publications by R on The broken bridge between biologists and statisticians
Some everyday data tasks: a few hints with R
We all work with data frames and it is important that we know how we can reshape them, as necessary to meet our needs. I think that there are, at least, four routine tasks that we need to be able to accomplish: subsetting sorting casting melting Obviously, there is a wide array of possibilities; I’ll just mention a few, which I regularly use....
4079 sym R (7476 sym/17 pcs)
How do we combine errors? The linear case
In our research work, we usually fit models to experimental data. Our aim is to estimate some biologically relevant parameters, together with their standard errors. Very often, these parameters are interesting in themselves, as they represent means, differences, rates or other important descriptors. In other cases, we use those estimates to deriv...
6229 sym R (1982 sym/8 pcs)
Dealing with correlation in designed field experiments: part I
Observations are grouped When we have recorded two traits in different subjects, we can be interested in describing their joint variability, by using the Pearson’s correlation coefficient. That’s ok, altough we have to respect some basic assumptions (e.g. linearity) that have been detailed elsewhere (see here). Problems may arise when we nee...
7048 sym R (2546 sym/5 pcs)
Dealing with correlation in designed field experiments: part I
Observations are grouped When we have recorded two traits in different subjects, we can be interested in describing their joint variability, by using the Pearson’s correlation coefficient. That’s ok, altough we have to respect some basic assumptions (e.g. linearity) that have been detailed elsewhere (see here). Problems may arise when we nee...
7048 sym R (2546 sym/5 pcs)
Dealing with correlation in designed field experiments: part II
With field experiments, studying the correlation between the observed traits may not be an easy task. Indeed, in these experiments, subjects are not independent, but they are grouped by treatment factors (e.g., genotypes or weed control methods) or by blocking factors (e.g., blocks, plots, main-plots). I have dealt with this problem in a previous...
10687 sym R (15935 sym/19 pcs)
Dealing with correlation in designed field experiments: part II
With field experiments, studying the correlation between the observed traits may not be an easy task. Indeed, in these experiments, subjects are not independent, but they are grouped by treatment factors (e.g., genotypes or weed control methods) or by blocking factors (e.g., blocks, plots, main-plots). I have dealt with this problem in a previous...
10688 sym R (15949 sym/19 pcs)
How do we combine errors, in biology? The delta method
In a recent post I have shown that we can build linear combinations of model parameters (see here ). For example, if we have two parameter estimates, say Q and W, with standard errors respectively equal to \(\sigma_Q\) and \(\sigma_W\), we can build a linear combination as follows: \[Z = AQ + BW + C\] where A, B and C are three coefficients. The ...
7240 sym R (1523 sym/15 pcs) 2 img
How do we combine errors, in biology? The delta method
In a recent post I have shown that we can build linear combinations of model parameters (see here ). For example, if we have two parameter estimates, say Q and W, with standard errors respectively equal to \(\sigma_Q\) and \(\sigma_W\), we can build a linear combination as follows: \[Z = AQ + BW + C\] where A, B and C are three coefficients. The ...
7240 sym R (1523 sym/15 pcs) 2 img
Genotype experiments: fitting a stability variance model with R
Yield stability is a fundamental aspect for the selection of crop genotypes. The definition of stability is rather complex (see, for example, Annichiarico, 2002); in simple terms, the yield is stable when it does not change much from one environment to the other. It is an important trait, that helps farmers to maintain a good income in most years...
7965 sym R (3576 sym/7 pcs)
Genotype experiments: fitting a stability variance model with R
Yield stability is a fundamental aspect for the selection of crop genotypes. The definition of stability is rather complex (see, for example, Annichiarico, 2002); in simple terms, the yield is stable when it does not change much from one environment to the other. It is an important trait, that helps farmers to maintain a good income in most years...
7965 sym R (3207 sym/7 pcs)