November 24, 2014

Stat of the Week Competition: November 22 – 28 2014

Each week, we would like to invite readers of Stats Chat to submit nominations for our Stat of the Week competition and be in with the chance to win an iTunes voucher.

Here’s how it works:

  • Anyone may add a comment on this post to nominate their Stat of the Week candidate before midday Friday November 28 2014.
  • Statistics can be bad, exemplary or fascinating.
  • The statistic must be in the NZ media during the period of November 22 – 28 2014 inclusive.
  • Quote the statistic, when and where it was published and tell us why it should be our Stat of the Week.

Next Monday at midday we’ll announce the winner of this week’s Stat of the Week competition, and start a new one.

(more…)

November 20, 2014

Not a good look

Clinical trials involve experimenting on humans, and so you want them to involve the minimum number of people and use the information as efficiently as possible. Part of that is committing in advance to what you expect the benefits of a treatment to be (the ‘primary endpoint’). If you got to look at the data first, and search for a favorable difference between the treated and untreated people you’d need a lot more evidence to convince people. That’s why clinical trial registration is important.

Derek Lowe, at In the Pipeline, has an unfortunate example of from biotech company studying stem cells in heart disease. Last year, the registration information at ClinicalTrials.gov said

To determine safety and the effect of intracoronary infusion of AMR-001 on myocardial perfusion (RTSS), measured by gated SPECT MPI at baseline and six months in subjects post-STEMI

and

primary endpoint includes safety of bone marrow procurement (measured by adverse events) and AMR-001 cell infusion (including incidence of re-stenosis and stent thrombosis in addition to other adverse events) as well as efficacy measured by quantitative by gated SPECT MPI specifically looking at resting total severity score)

On November 17 this year it changed

To determine safety and efficacy of intracoronary infusion of NBS10.

and

The primary endpoint includes the occurrence of AE’s, SAE’s and Major Adverse Cardiac Events (MACE) and the assessment of myocardial perfusion measured by quantitative gated SPECT MPI specifically looking at resting total severity score.

From the company’s press release

  • A statistically significant mortality benefit (p<0.05) in patients treated with NBS10 (also known as AMR-001) as compared to the placebo group; there were no deaths in the treatment group.
     
  • A statistically significant dose-dependent reduction in SAEs (p<0.05).
  • Observation of a dose-dependent numerical decrease in MACE. MACE occurred in 14% of control subjects, in 17% of subjects of who received less than 14 million CD34 cells, in 10% of subjects who received greater than 14 million CD34 cells, and in 7% of subjects who received greater than 20 million CD34 cells.
  • No meaningful difference in perfusion, as evidenced by SPECT imaging, between the treatment and the control group from baseline to 6 months in resting total severity score (RTSS) suggesting this may not be a future suitable tool to assess NBS10, which is consistent with U.S. Food and Drug Administration (FDA) guidance that mortality and MACE are the appropriate approvable endpoints to determine efficacy of a cellular therapy for cardiac disease as opposed to imaging endpoints. 

That is, the trial failed to show a change where there were looking for one,  but found evidence for a reduction in other things — apparently after they knew the results.

Round numbers

Nature doesn’t care about round numbers in base 10, but people do.  From @rcweir, via Amy Hogan, this is Twitter data of the number of people followed and following (truncated at 1000 to be readable). The number of people you follow is under your control, and there are clear peaks at multiples of 100 (and perhaps at multiples of 10 below 100). The number following you isn’t under your control, and there aren’t any similar patterns.

twit

 

For a medical example, here are self-reported weights from the US National Health Interview Survey

nhis-wt

The same thing happens with measured variables that are subject to operator error: blood pressure, for example, shows fairly strong digit preference unless a lot of care is taken in the measurement.

November 18, 2014

What do statisticians do all day?

As usual about this time of year, our Honours and M.Sc. students are giving talks on their research projects

  • Modelling the natural inflows to New Zealand lakes
  • Refactoring the xtable package
  • Invertible reproducible documents
  • Bootstrap goodness of fit tests
  • Convex regression
  • Using the Robust Covariance Matrix Estimator to improve the precision of principal component eigenvectors in the orthogonal multivariate test
  • Orthogonalised multivariate survey-weighted linear models for medical data
  • Factors affecting catch composition in NZ scampi fisheries
  • Factors affecting tagging mortality in snapper
  • Assessment of rapid eradication assessment
  • Factors explaining the low income return for education among Asian New Zealanders
  • A comparison of methods used to reconcile forecasts in hierarchical time series
  • Numerical methods for drawing piecewise smooth curves
  • An evaluation of the Christian Broadcasting Association’s Appeal and Donorcom campaigns
  • Multi-choice and true/false assessments in introductory statistics: What can they tell us about student understanding?
  • Bayesian computation for exoplanet data
  • Modelling an Ophthalmology Clinic Booking List System: Assumptions and Implementation
  • Reinforcement Processes on Graphs
  • Influence analysis on phylogeny inference
  • Statistical analysis of chemical soil composition in the Wairau Valley
  • Describing the world’s nations
  • Parameter estimation of the coalescent in continuous space

Cholesterol is bad for you

That doesn’t sound like a very interesting headline, but an important clinical trial whose results were released today has made definite steps towards re-convincing researchers on this point.

The trial, IMPROVE-IT, looked at adding a new drug, ezetimibe, to one of the standard statin drugs for cholesterol lowering, in people who had previously had a heart attack. Ezetimibe works by blocking cholesterol absorption in the gut, a completely different mechanism to the statins, which block cholesterol synthesis. The drug had previously shown unconvincing results in a preliminary study, made even less convincing by the behaviour of the manufacturer. There was increasing uncertainty that the cholesterol-lowering effect of the statins was really how they prevented heart disease, since no other drug appeared to be able to do the same thing.

Now, IMPROVE-IT has found a reduction in heart attacks and strokes. It’s very small — only 2 percentage points, even in this high-risk group of patients — but it looks real. Given the price of ezetimibe it probably won’t be widely used immediately, but it comes off patent in a few years and then use might spread a bit.  The results are also encouraging for dietary approaches to lowering cholesterol by reducing absorption: some cereals, and spreads with plant sterols.

Other stories: Forbes, New York Times 

November 17, 2014

Stat of the Week Competition: November 15 – 21 2014

Each week, we would like to invite readers of Stats Chat to submit nominations for our Stat of the Week competition and be in with the chance to win an iTunes voucher.

Here’s how it works:

  • Anyone may add a comment on this post to nominate their Stat of the Week candidate before midday Friday November 21 2014.
  • Statistics can be bad, exemplary or fascinating.
  • The statistic must be in the NZ media during the period of November 15 – 21 2014 inclusive.
  • Quote the statistic, when and where it was published and tell us why it should be our Stat of the Week.

Next Monday at midday we’ll announce the winner of this week’s Stat of the Week competition, and start a new one.

(more…)

November 16, 2014

John Oliver on the lottery

When statisticians get quoted on the lottery it’s pretty boring, even if we can stop ourselves mentioning the Optional Stopping Theorem.

This week, though, John Oliver took on the US state lotteries: “..,more than Americans spent on movie tickets, music, porn, the NFL, Major League Baseball, and video games combined. “

(you might also look at David Fisher’s Herald stories on the lottery)

November 14, 2014

Motion and context in graphics

Via Michael Toth  I found this animated GIF from isomorphismes, showing the ‘yield curve‘ for Federal Reserve bonds

tumblr_na17r44bUx1qc38e9o1_400

Michael modified the curve to make it prettier — alternatively, more similar to the style of The Economist.  In both cases, though, I felt the time context was missing.  Using animation rather than multiple plots lets you get a lot more on a page, but you can’t see what’s happening as clearly.

One possibility is to make a separate graphic that shows where you are in time; another is to keep some history by letting the graph leave shadows. In the graph below (based on both the linked examples), there are 12 months worth of shadow lines trailing the solid line, and a grey indicator bar showing where we are in history, with GDP growth and unemployment as context.

yield curve evolution

Even better (though not embeddable in WordPress) would be to make the time axis able to both autoplay and be controllable by the user, as in this example from the R animint package.

 

(update: the code)

November 13, 2014

School deciles

New Zealand has a national school funding system that allocates money to schools based on socio-economic data about students.  This isn’t self-reported individual-level data, but is at the level of Census meshblocks (details here.) Schools are divided into ten deciles, and more funding given to lower-decile schools.  Despite the higher funding, lower-decile schools, on average, have poorer results on standardised assessments.  You can see good visualisations of this from Luis Apiolaza,

mathOK

There are less-good ones at Stuff: dot plots aren’t ideal for this, and it really is better to look at cumulative categories (‘at standard or better’) rather than individual categories (‘at standard but not better’). Unfortunately, these graphs tell you almost nothing about the policy question of whether there are better ways to target the funding. There might be; there might not be.

One advantage of the current system is its automatic stabilisation. The Herald, earlier this week, had a good story about changing ethnic profiles of schools, with the sort of combination of data and individual stories it would be nice to see more often.  It turns out the low-decile schools are seeing fewer students of European ethnicity, and more Māori and Pasifika students. The phrase ‘white flight’ was used, but because of the funding system this isn’t the same sort of problem as the original ‘white flight’ from US inner cities.

In the US, a lot of public school funding comes from local government. When more-affluent families leave an area, the government funding for education goes down.  In New Zealand, when more-affluent families leave an area, the government funding for education goes up.  There’s still a concern about diversity, but not the same sort of vicious circle that was seen in the US.

November 12, 2014

Africa? Can you be more precise?

From the Telegraph (via many people on Twitter)

ebola

 

Seeing this at the same time as hearing about Bob Geldof’s Band-Aid reboot really emphasises the point that Africa isn’t a single place. The first Band-Aid recording was intended to help people in Ethiopia; the new one is for the Ebola-stricken regions of West Africa. The distance from Freetown to Addis Ababa is about the same as Auckland to Dili in East Timor, or Los Angeles to Bogota (or Addis Ababa to Prague).

On the other hand, the graph does make an important point. Syphilis, starvation, and TB are all very inexpensively treatable. Malaria and HIV are largely preventable, also at low cost. An effective treatment for Ebola will help, especially for medical personnel who are otherwise at very high risk, but in the long run it isn’t going to be enough. If we can’t deliver penicillin effectively, we won’t be able to deliver Ebola drugs. To make a real difference, we need a vaccine that’s good enough to prevent outbreaks.