269 search results for "anova"

R intro seminars, take 2: some slides about data frames, linear models and statistical graphics

November 7, 2013
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R intro seminars, take 2: some slides about data frames, linear models and statistical graphics

I am doing a second installment of the lunch seminars about data analysis with R for the members of the Wright lab. It’s pretty much the same material as before — data frames, linear models and some plots with ggplot2 — but I’ve sprinkled in some more exercises during the seminars. I’ve tried emphasising scripting a

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Statistical aspects of two-way cross-over studies

November 3, 2013
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I ran into this presentation on Statistical aspects of two-way cross-over studies by Ing. Helmut Schütz (http://bebac.at). He presented some code and referred to the bear package. The bear package is menu driven, which is not my thing. I had to try and do that in R via other packages. The aim is to estimate if the...

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How Do You Write Your Model Definitions?

October 20, 2013
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How Do You Write Your Model Definitions?

I’m often irritated by that when a statistical method is explained, such as linear regression, it is often characterized by how it can be calculated rather than by what model is assumed and fitted. A typical example of this is that linear regression is often described as a method that uses ordinary least squares to calculate the best...

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Science at the speed of ligth

October 15, 2013
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Science at the speed of ligth

May be is not going that fast, but at the speed of R at least. And R is pretty quick. This has pros and cons. I think that understanding the drawbacks is key to maximize the good things of speed, … Continue reading →

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“Statistical Models with R” Course – Milano, October 24-25, 2013

September 19, 2013
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MilanoR, in collaboration with Quantide, organizes "Statistical Models with R" Course October 24-25, 2013 Course description This two-day course shows a wide variety of statistical models with R ranging from Linear Models (LM) to Generalized Linear Models (GLM) modelling, in … Continue reading →

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informative hypotheses (book review)

September 18, 2013
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informative hypotheses (book review)

The title of this book Informative Hypotheses somehow put me off from the start: the author, Hebert Hoijtink, seems to distinguish between informative and uninformative (deformative? disinformative?) hypotheses. Namely, something like H0: μ1=μ2=μ3=μ4 is “very informative” and the alternative Ha is completely uninformative, while the “alternative null” H1: μ1<μ2=μ3<μ4 is informative. (Hence the < signs on

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Mixed models; Random Coefficients, part 2

September 14, 2013
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Continuing from random coefficients part 1, it is time for the second part. To quote the SAS/STAT manual 'a random coefficients model with error terms that follow a nested structure'. The additional random variable is monthc, which is a factor con...

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Mixed models; Random Coefficients, part 1

September 8, 2013
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Mixed models; Random Coefficients, part 1

Continuing with my exploration of mixed models I am now at the first part of random coefficients: example 59.5 for proc mixed (page 5034 of the SAS/STAT 12.3 Manual). This means I skipped examples 59.3 (plotting the likelihood) and 59.4 (known G and R)...

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Latent Variable Analysis with R: Getting Setup with lavaan

September 1, 2013
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Latent Variable Analysis with R: Getting Setup with lavaan

Getting Started with Structural Equation Modeling Part 1Getting Started with Structural Equation Modeling: Part 1 Introduction For the analyst familiar with linear regression fitting structural equation models can at first feel strange. In the R environment, fitting structural equation models involves learning new modeling syntax, new plotting...

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The joy and martyrdom of trying to be a Bayesian

August 30, 2013
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Some of my fellow scientists have it easy. They use predefined methods like linear regression and ANOVA to test simple hypotheses; they live in the innocent world of bivariate plots and lm(). Sometimes they notice that the data have odd histograms and they use glm(). The more educated ones use … Continue reading →

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