282 search results for "ANOVA"

Gradient Boosting: Analysis of LendingClub’s Data

April 8, 2013
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Gradient Boosting: Analysis of LendingClub’s Data

An old 5.75% CD of mine recently matured and seeing that those interest rates are gone forever, I figured I’d take a statistical look at LendingClub’s data. Lending Club is the first peer-to-peer lending company to register its offerings as securities with the Securities and Exchange Commission (SEC). Their operational statistics are public and available for download. The latest

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R 3.0.0 is released! (what’s new, and how to upgrade)

April 3, 2013
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R 3.0.0 is released! (what’s new, and how to upgrade)

A few hours ago Peter Dalgaard (of R Core Team) announced the release of R 3.0.0!  Bellow you can read the changes in this release. One of the features worth noticing is the introduction of long vectors to R 3.0.0. As David Smith …Read more »

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Veterinary Epidemiologic Research: GLM – Logistic Regression (part 2)

March 17, 2013
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Veterinary Epidemiologic Research: GLM – Logistic Regression (part 2)

Second part on logistic regression (first one here). We used in the previous post a likelihood ratio test to compare a full and null model. The same can be done to compare a full and nested model to test the contribution of any subset of parameters: Interpretation of coefficients Note: Dohoo do not report the

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Ordinal Data

March 17, 2013
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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...

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Veterinary Epidemiologic Research: GLM – Logistic Regression

March 14, 2013
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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

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R to Latex packages: Coverage

March 12, 2013
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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.

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

March 11, 2013
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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

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A slightly different introduction to R, part IV

February 21, 2013
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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

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Better modelling and visualisation of newspaper count data

February 19, 2013
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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...

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

February 18, 2013
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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 →

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