“Reproducible research” is a hot question

I have long been interested in the question of reproducible research and as a manuscript author, reviewer and more recently, editor, have attempted to make sure that no key information was missing and that methods were described in full detail and, of course, valid.

Although the problem has always existed, I think that in recent years papers and reports with badly described methods have become more frequent. I think that there are many reasons for this: 1) the pressure to publish quickly and frequently as a condition for career advance, 2) the overload on reviewers work’ and the pressure from journals to get manuscript reviews submitted within a few days’ time, 3) the stricter and stricter rules of journals about maximum number of “free” pages, and 4) the practice by some journals of publishing methods at the end of the papers or in smaller typeface, implying that methods are not important for most readers, and irrelevant for understanding the results described (which is a false premise).

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New updates

The most important of these updates is that to package photobiology, which is now at version 0.3.7. The main changes have to do with spectral objects and operators for them. A lot of testing and debugging was done, and a few functions and a data sets added.

Package photobiologyFilters, which is now at version 0.1.12 had some minor fixes and data additions. The ‘catalogue of filters’ has been updated.

Package photobiologyLamps, which is now at version 0.1.12 includes the same data as earlier but the code has been updated so that only spectral energy irradiance is stored in the spectral objects.


Since a few updates back, I have gradually changed the code to use data tables instead of data frames. Data tables are defined in package data.table, which is now required. However, the current release of data.table has a bug that breaks the code in my packages. This bug is fixed in the current development version of data.table, but this version (1.9.3) is not available through CRAN. I have built it and uploaded to the r4photo repository where my packages are.

Some frequent ways of unwillingly misrepresenting experimental results

Many students and some researchers are ignorant of the fact that any of the following practices are statistically invalid and could be considered to be ‘research-results manipulation’ (=cheating):

  1. Repeating an experiment until the p-value becomes significant.
  2. Reporting only a ‘typical’ (=nice-looking) replication of the experiment, and presenting statistics (tests of significance and/or parameter estimates such as means and standard errors) based only on this subset of the data.
  3. Presenting a subset of the data chosen using a subjective criterion.
  4. Not reporting that outliers have been removed from the data presented or used in analyses.