Publications by Christos Argyropoulos
Table as an image in R
http://www.r-bloggers.com/table-as-an-image-in-r/ Useful when cramming data into multipanel images and do not feel like toiling away in LATeX Related To leave a comment for the author, please follow the link and comment on their blog: Statistical Reflections of a Medical Doctor » R. R-bloggers.com offers daily e-mail updates about R news a...
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Failed Randomization In A Randomized Trial?
We will continue the saga of the three-arm clinical trial that is giving the editors of the prestigious journal The Spleen a run for their money. While the polls are gathering digital dust, let’s see if we can direct this discussion to a more quantitative path. To do so, we will ask (and answer) the question from a frequentist point; according ...
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Page Rev Bayes – we found statistical irregularities in a randomized controlled trial
The Bayesian counterpart to the frequentist analysis of the Randomized Controlled Trial is in many aspects more straightforward than the Bayesian analysis. One starts with a prior probability about the probability of a patient being assigned to each of the three arms and combines it with the (multinomial) likelihood of observing a given assignmen...
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Extracting standard errors and treatment effects from medical journal tables (powered by R)
I decided to start blogging the R code used for some of my statistical posts, so I will start with the meta-analysis posts and move on to more difficult stuff. As stated previously (here and here) the problem is to convert the reported relative risks(RR, ), 95% confidence interval () and p-value () into estimates for the log-relative risk ratio a...
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Bayesian linear regression analysis without tears (R)
Bayesian methods are sure to get some publicity after Vale Johnson’s PNAS paper regarding the use of Bayesian approaches to recalibrate p-value cutoffs from 0.05 to 0.005. Though the paper itself is bound to get some heat (see the discussion in Andrew Gelman’s blog and Matt Briggs’s fun-to-read deconstruction), the controversy might stimula...
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Bayesian Linear Regression Analysis (with non-informative priors but without Monte Carlo) In R
Continuing the previous post concerning linear regression analysis with non-informative priors in R, I will show how to derive numerical summaries for the regression parameters without Monte Carlo integration. The theoretical background for this post is contained in Chapter 14 of Bayesian Data Analysis which should be consulted for more informat...
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The little non-informative prior that could (be informative)
Christian Robert reviewed on line a paper that was critical of non-informative priors. Among the points that were discussed by him and other contributors (e.g. Keith O’Rourke), was the issue of induced priors, i.e. priors which arise from a transformation of original parameters, or of observables. I found this exchange interesting because I did...
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Survival Analysis With Generalized Additive Models : Part I (background and rationale)
After a really long break, I’d will resume my blogging activity. It is actually a full circle for me, since one of the first posts that kick started this blog, matured enough to be published in a peer-reviewed journal last week. In the next few posts I will use the R code included to demonstrate the survival fitting capabilities of Generalized...
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Survival Analysis With Generalized Models: Part II (time discretization, hazard rate integration and calculation of hazard ratios)
In the second part of the series we will consider the time discretization that makes the Poisson GAM approach to survival analysis possible. Consider a set of s individual observations at times , with censoring indicators assuming the value of 0 if the corresponding observation was censored and 1 otherwise. Under the assumption of non-informativ...
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Survival Analysis With Generalized Additive Models : Part III (the baseline hazard)
In the third part of the series on survival analysis with GAMs we will review the use of the baseline hazard estimates provided by this regression model. In contrast to the Cox mode, the log-baseline hazard is estimated along with other quantities (e.g. the log hazard ratios) by the Poisson GAM (PGAM) as: In the aforementioned expression, the ba...
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