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Veterinary Epidemiologic Research: GLM – Evaluating Logistic Regression...
Third part on logistic regression (first here, second here). Two steps in assessing the fit of the model: first is to determine if the model fits using summary measures of goodness of fit or by...
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Veterinary Epidemiologic Research: GLM (part 4) – Exact and Conditional...
Next topic on logistic regression: the exact and the conditional logistic regressions. Exact logistic regression When the dataset is very small or severely unbalanced, maximum likelihood estimates of...
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Veterinary Epidemiologic Research: Count and Rate Data – Poisson & Negative...
Still going through the book Veterinary Epidemiologic Research and today it’s chapter 18, modelling count and rate data. I’ll have a look at Poisson and negative binomial regressions in R. We use count...
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Veterinary Epidemiologic Research: Count and Rate Data – Zero Counts
Continuing on the examples from the book Veterinary Epidemiologic Research, we look today at modelling count when the count of zeros may be higher or lower than expected from a Poisson or negative...
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Veterinary Epidemiologic Research: Count and Rate Data – Poisson Regression...
As noted on paragraph 18.4.1 of the book Veterinary Epidemiologic Research, logistic regression is widely used for binary data, with the estimates reported as odds ratios (OR). If it’s appropriate for...
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Veterinary Epidemiologic Research: Modelling Survival Data – Non-Parametric...
Next topic from Veterinary Epidemiologic Research: chapter 19, modelling survival data. We start with non-parametric analyses where we make no assumptions about either the distribution of survival...
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Veterinary Epidemiologic Research: Modelling Survival Data – Semi-Parametric...
Next on modelling survival data from Veterinary Epidemiologic Research: semi-parametric analyses. With non-parametric analyses, we could only evaluate the effect one or a small number of variables. To...
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Veterinary Epidemiologic Research: Modelling Survival Data – Parametric and...
Last post on modelling survival data from Veterinary Epidemiologic Research: parametric analyses. The Cox proportional hazards model described in the last post make no assumption about the shape of the...
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Bias in Observational Studies – Sensitivity Analysis with R package episensr
When it’s time to interpret the study results from your observational study, you have to estimate if the effect measure you obtained is the truth, if it’s due to bias (systematic error, the effect...
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Factor Analysis in Epidemiology
This is a short (15′!) presentation given for the Canadian Veterinary Epidemiology Club (CVEC) on February 26, 2016, about new epi tools. What is Factor Analysis? Factor analysis is a group of...
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