269 search results for "ANova"

Ordinal Data

March 17, 2013
By
Ordinal Data

I expect to be getting some ordinal data, from 5 or 9 point rating scales, pretty soon, so I am having a look ahead how to treat those. Often ANOVA is used, even though it is well known not to be ideal fro a statistical point of view, so that is the st...

Read more »

Veterinary Epidemiologic Research: GLM – Logistic Regression

March 14, 2013
By
Veterinary Epidemiologic Research: GLM – Logistic Regression

We continue to explore the book Veterinary Epidemiologic Research and today we’ll have a look at generalized linear models (GLM), specifically the logistic regression (chapter 16). In veterinary epidemiology, often the outcome is dichotomous (yes/no), representing the presence or absence of disease or mortality. We code 1 for the presence of the outcome and 0

Read more »

R to Latex packages: Coverage

March 12, 2013
By

There are now quite a few R packages to turn cross-tables and fitted models into nicely formatted latex. In a previous post I showed how to use one of them to display regression tables on the fly. In this post I summarise what types of R object each of the major packages can deal with.

Read more »

Veterinary Epidemiologic Research: Linear Regression Part 3 – Box-Cox and Matrix Representation

March 11, 2013
By
Veterinary Epidemiologic Research: Linear Regression Part 3 – Box-Cox and Matrix Representation

In the previous post, I forgot to show an example of Box-Cox transformation when there’s a lack of normality. The Box-Cox procedure computes values of which best “normalises” the errors. value Transformed value of Y 2 1 0.5 0 -0.5 -1 -2 For example: The plot indicates a log transformation. Matrix Representation We can use

Read more »

A slightly different introduction to R, part IV

February 21, 2013
By
A slightly different introduction to R, part IV

Now, after reading in data, making plots and organising commands with scripts and Sweave, we’re ready to do some numerical data analysis. If you’re following this introduction, you’ve probably been waiting for this moment, but I really think it’s a good idea to start with graphics and scripting before statistical calculations. We’ll use the silly

Read more »

Better modelling and visualisation of newspaper count data

February 19, 2013
By
Better modelling and visualisation of newspaper count data

<!-- Styles for R syntax highlighter In this post I outline how count data may be modelled using a negative binomial distribution in order to more accurately present trends in time series count data than using linear methods. I also show how to...

Read more »

Predictors, responses and residuals: What really needs to be normally distributed?

February 18, 2013
By
Predictors, responses and residuals: What really needs to be normally distributed?

Introduction Many scientists are concerned about normality or non-normality of variables in statistical analyses. The following and similar sentiments are often expressed, published or taught: "If you want to do statistics, then everything needs to be normally distributed." "We normalized…Read more →

Read more »

Veterinary Epidemiologic Research: Linear Regression

February 14, 2013
By
Veterinary Epidemiologic Research: Linear Regression

This post will describe linear regression as from the book Veterinary Epidemiologic Research, describing the examples provided with R. Regression analysis is used for modeling the relationship between a single variable Y (the outcome, or dependent variable) measured on a continuous or near-continuous scale and one or more predictor (independent or explanatory variable), X. If

Read more »

Taking Expectations to the Next Level

January 31, 2013
By
Taking Expectations to the Next Level

Higher Expectations I came across this post on Thursday and found it to be quite interesting. Clearly rental prices vary according to where you live. That isn't too surprising. I started thinking a bit more about it and thought that Boston and the nearby communities would have to...

Read more »

Maximize Your Expectations!

January 30, 2013
By
Maximize Your Expectations!

A Problem A major problem in secondary data analysis is that you didn't get to decide what data was collected. Lets say you were interested in how many times a student has read the Twilight books). Specifically, you want to know how effective the ads for...

Read more »