Some doctors receive more malpractice reports than others. Just how unequal is the distribution of malpractice reports?
The post 1.5 percent of doctors, a quarter of malpratice reports appeared first on Decision Science News.
R posts in other languages
- 适合初学者的R语言教程
- SAS hat einen neuen Vergleich von SAS und R veröffentlicht
- 实现可重复的统计slides
- О связи между “утечкой мозгов” и объемом пассажирских перевозок
- Новая книга по основам прогнозирования (с использованием R)
- Двухфакторный дисперсионный анализ
- Revolution R Enterprise 6.2 mit neuen Funktionen für hoch performante Analysen auf Big Data
- Third Milano R net meeting: leave a comment
- Photos of the third Milano R net meeting
- Presentations of the third Milano R net meeting
SIR Model – The Flue Season – Dynamic Programming
# The SIR Model (susceptible, infected, and recovered) model is a common and useful tool in epidemiological modelling.
# In this post and in future posts I hope to explore how this basic model can be enriched by including different population groups or disease vectors.
# Simulation Population Parameters:
# Proportion Susceptible
Sp = .9
# Proportion...
Much more efficient bubble sort in R using the Rcpp and inline packages
Recently I wrote a blogpost showing the implementation of a simple bubble sort algorithm in pure R code. The downside of that implementation was that is was awfully slow. And by slow, I mean really slow, as in “a 100… See more ›
Beware: 2 is not always 2 in R
This post is minimalistic. Consider this: Now let's have look at what's inside x: But is it really true? Here you go. A colleague of mine was once ruined by this for an entire day before we realized what was…
Forecast Update: Will 2014 be the Beginning of the End for SAS and SPSS?
I recently updated my plots of the data analysis tools used in academia in my ongoing article, The Popularity of Data Analysis Software. I repeat those here and update my previous forecast of data analysis software usage. Learning to use … Continue reading →
Projection Pursuit Classification Trees
I've been looking at this article for a new tree-based method. It uses other classification methods (e.g. LDA) to find a single variable use in the split and builds a tree in that manner. The subtleties of the model are: The model does not prune but ...
PhyloTempo
Summary: Two new measures of tree topology are introduced: temporal clustering (TC), and staircase-ness. Several other existing statistics are also implemented for the purpose of comparison: Aldous's graphical test and likelihood test to decide if a tree fits the Yule … Continue reading →
The rbinding race: for vs. do.call vs. rbind.fill
Which function rbinds dataframes together fastest?First competitor: classic rbind in a for loop over a list of dataframesSecond competitor: do.call("rbind", <list of dataframes>)Third competitor: rbind.fill(<list of dataframes>) f...
Visualizing your websites’ ecommerce performance with R
In this blogpost, I want to dive deeper into the explanation of the relationship between Frequency and Recency of Visits with the Conversion Rate and Average Order Value. I have used the RGA package for data extraction and Dr. Hadley Wickham’s ggplot2 package to achieve the visualizations. Here’s the data aggregation script : #transactions dataframe
Claims Inflation – a known unknown
Over the last year I worked with two colleagues of mine on the subject of inflation and claims inflation in particular. I didn't expect it to be such a challenging topic, but we ended up with more questions than answers. The key question and biggest ch...
RcppArmadillo 0.3.820
Conrad rolled up a new Armadillo release 3.820 (following two minor fix release in the 0.3.810 series of which we packaged the one that was relevant for us). This new version is now out in a release 0.3.820 of RcppArmadillo which is already on CRAN a...
Stan!
Guy Freeman writes: I thought you’d all like to know that Stan was used and referenced in a peer-reviewed Rapid Communications paper on influenza. Thank you for this excellent modelling language and sampler, which made it possible to carry out this work quickly! I haven’t actually read the paper, but I’m happy to see Stan
The post Stan!...
Ｒによるモンテカルロ法入門
Here is the cover of the Japanese translation of our Introducing Monte Carlo methods with R book. A few year after the French translation. It actually appeared last year in August but I was not informed of this till a few weeks ago. The publisher is Maruzen, with an associated webpage if you want to 
Integration take two – Shiny application
My last post discussed a technique for integrating functions in R using a Monte Carlo or randomization approach. The mc.int function (available here) estimated the area underneath a curve by multiplying the proportion of random points below the curve by the total area covered by points within the interval: The estimated integration (bottom plot) is 
In case you missed it: April 2013 Roundup
In case you missed them, here are some articles from April of particular interest to R users: A critique of a SAS whitepaper comparing the performance of SAS, R and Mahout. A video presentation from statistician Tess Nesbitt at UpStream, who uses GAM survival models in R for marketing attribution analysis. The April edition of the Revolution Analytics newsletter....
Shiny App for CRAN packages
Over the past few days, I have been introduced to a few new-to-me R packages, via some comments from the Shiny guys and the R-bloggers site. This seems a rather haphazard way of acquiring knowledge and I cannot be alone in thinking that this is not the most productive way to become aware of new/better
Stack Exchange: Why I dropped out
Stack Exchange is a series of question-and-answer sites, including Stack Overflow for programming and Cross Validated for statistics. I was introduced to these sites at a short talk by Barry Rowlingson at the 2011 UseR! meeting, “Why R-help must die!“ These sites have a lot of advantages over R-help: The format is easier to read, 
The Power of the Evaluate, Parse, Paste Combination
# The Power of the Evaluate, Parse, Paste combination# One of the powerful features of Stata which I have missed the most when working with R is the absence of the Stata Macros that allow the user to construct bits of Stata code from anything and combi...
Global Indicator Analyses with R
I was recently asked by a client to create a large number of “proof of concept” visualizations that illustrated the power of R for compiling and analyzing disparate datasets. The client was specifically interested in automated analyses of global data. A little research led me to the WDI package. The WDI package is a tool
The post Global...
Living it up with computational errors
How to have a better chance of a good outcome. Making mistakes There’s been a lot of talk recently about data analysis problems with spreadsheets. If you’ve not stuck your head out of your cave lately, then you can catch some of the discussion by doing an internet search for: Reinhart Rogoff There are several
The post Living...
The Guerilla Guide to R
Update: I am aware the table of contents are being displayed in bullet form as I intended. The web template I'm using seems to be buggy. It also seems to think this page is in Indonesian...Working on it!
Table of Contents:
Recent Rcpp talks at U of C and MCW
A couple of days ago, I had an opportunity to give a guest lecture on our Rcpp package for R and C++ integration. This was in CMSC 12300 Computer Science with Applications-3 in the Department of Computer Science at University of Chicago. The course i...
awalé
Following Le Monde puzzle #810, I tried to code an R program (not reproduced here) to optimise an awalé game but the recursion was too rich for R: even with a very small number of holes and seeds in the awalé… Searching on the internet, it seems the computer simulation of a winning strategy for 
Reshaping data
Preparing and reshaping data is the ever continuing task of a data analyst. Luckily we have many tools for it. The default tool in R would be reshape(), although this is so user friendly that a reshape package has been added too. I try to use reshape()...
Playing cards, with R
In my courses on R, I usually show how to insert a picture as a background for a graph. But it is also to see the picture as an object, and to insert it in a graph everywhere we like to see it, as explained on the awesome blog http://rsnippets.blogspot.ca/…. (in a post published in January 2012). I wanted...
Animations Understood
When I first saw a graphic made from Yihui’s animation package (Xie, 2012) I was amazed at the magic and thought “I could never do that”. Passage of time… One night I found myself bored and as usual avoiding work. … Continue reading →
Reproducibility and randomness
With Stéphane Tufféry, we were working this week on a chapter of a book, entitled Statistical Learning in Actuarial Science. The chapter should be based on R functions, and we wanted to reproduce some outputs he previously obtained with SAS. The good thing is that even complex functions (logistic regression, regression trees, etc) produce the same kind of outputs....
Veterinary Epidemiologic Research: Count and Rate Data – Poisson Regression and Risk Ratios
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 case-control studies, risk ratios (RR) are preferred for cohort studies as RR provides estimates of probabilities directly. Moreover, it is often forgotten the assumption 
Spatial Critter Swarming Simulation
(This article was first published on Econometrics by Simulation, and kindly contributed to R-bloggers) # I am interested in how small bits of individualized instructions can create collective action.# In this simulation I will give a single instruction to each individual in the swarm.# Choose another individual who is not too close, then accelerate towards that individual.# I also...
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
