# Articles by R on The broken bridge between biologists and statisticians

### Nonlinear combinations of model parameters in regression

January 8, 2020 |

Nonlinear regression plays an important role in my research and teaching activities. While I often use the ‘drm()’ function in the ‘drc’ package for my research work, I tend to prefer the ‘nls()’ function for teaching purposes, mainly because, in my...

### Nonlinear combinations of model parameters in regression

January 8, 2020 |

Nonlinear regression plays an important role in my research and teaching activities. While I often use the ‘drm()’ function in the ‘drc’ package for my research work, I tend to prefer the ‘nls()’ function for teaching purposes, mainly because, in my opinion, the transition from linear models to nonlinear models ...

### Fitting ‘complex’ mixed models with ‘nlme’: Example #4

September 12, 2019 |

Testing for interactions in nonlinear regression Factorial experiments are very common in agriculture and they are usually laid down to test for the significance of interactions between experimental factors. For example, genotype assessments may b...

### Fitting ‘complex’ mixed models with ‘nlme’: Example #2

September 12, 2019 |

A repeated split-plot experiment with heteroscedastic errors Let’s imagine a field experiment, where different genotypes of khorasan wheat are to be compared under different nitrogen (N) fertilisation systems. Genotypes require bigger plots, with r... [Read more...]

### Fitting ‘complex’ mixed models with ‘nlme’: Example #3

September 12, 2019 |

Accounting for the experimental design in regression analyses In this post, I am not going to talk about real complex models. However, I am going to talk about models that are often overlooked by agronomists and biologists, while they may be necessary in several circumstances, especially with field experiments. The ...

### Fitting ‘complex’ mixed models with ‘nlme’: Example #4

September 12, 2019 |

Testing for interactions in nonlinear regression Factorial experiments are very common in agriculture and they are usually laid down to test for the significance of interactions between experimental factors. For example, genotype assessments may be performed at two different nitrogen fertilisation levels (e.g. high and low) to understand whether ...

### Fitting ‘complex’ mixed models with ‘nlme’: Example #2

September 12, 2019 |

A repeated split-plot experiment with heteroscedastic errors Let’s imagine a field experiment, where different genotypes of khorasan wheat are to be compared under different nitrogen (N) fertilisation systems. Genotypes require bigger plots, with respect to fertilisation treatments and, therefore, the most convenient choice would be to lay-out the experiment ... [Read more...]

### Fitting ‘complex’ mixed models with ‘nlme’. Example #1

August 19, 2019 |

The environmental variance model Fitting mixed models has become very common in biology and recent developments involve the manipulation of the variance-covariance matrix for random effects and residuals. To the best of my knowledge, within the frame of frequentist methods, the only freeware solution in R should be based on ... [Read more...]

### Fitting ‘complex’ mixed models with ‘nlme’. Example #1

August 19, 2019 |

The environmental variance model Fitting mixed models has become very common in biology and recent developments involve the manipulation of the variance-covariance matrix for random effects and residuals. To the best of my knowledge, within the fra... [Read more...]

### Germination data and time-to-event methods: comparing germination curves

July 19, 2019 |

Very often, seed scientists need to compare the germination behaviour of different seed populations, e.g., different plant species, or one single plant species submitted to different temperatures, light conditions, priming treatments and so on. How ...

### Germination data and time-to-event methods: comparing germination curves

July 19, 2019 |

Very often, seed scientists need to compare the germination behaviour of different seed populations, e.g., different plant species, or one single plant species submitted to different temperatures, light conditions, priming treatments and so on. How should such a comparison be performed? Let’s take a practical approach and start ...

### Germination data and time-to-event methods: comparing germination curves

July 19, 2019 |

Very often, seed scientists need to compare the germination behaviour of different seed populations, e.g., different plant species, or one single plant species submitted to different temperatures, light conditions, priming treatments and so on. How ...

### Survival analysis and germination data: an overlooked connection

The background Seed germination data describe the time until an event of interest occurs. In this sense, they are very similar to survival data, apart from the fact that we deal with a different (and less sad) event: germination instead of death. B...

### Survival analysis and germination data: an overlooked connection

The background Seed germination data describe the time until an event of interest occurs. In this sense, they are very similar to survival data, apart from the fact that we deal with a different (and less sad) event: germination instead of death. But, seed germination data are also similar to ...

### Survival analysis and germination data: an overlooked connection

The background Seed germination data describe the time until an event of interest occurs. In this sense, they are very similar to survival data, apart from the fact that we deal with a different (and less sad) event: germination instead of death. B...

### Stabilising transformations: how do I present my results?

June 14, 2019 |

ANOVA is routinely used in applied biology for data analyses, although, in some instances, the basic assumptions of normality and homoscedasticity of residuals do not hold. In those instances, most biologists would be inclined to adopt some sort of stabilising transformations (logarithm, square root, arcsin square root…), prior to ANOVA. ...

### Stabilising transformations: how do I present my results?

June 14, 2019 |

ANOVA is routinely used in applied biology for data analyses, although, in some instances, the basic assumptions of normality and homoscedasticity of residuals do not hold. In those instances, most biologists would be inclined to adopt some sort of ...

### 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 ... [Read more...]

### 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 ... [Read more...]

### 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...