Clear Comparisons Make Your Data Meaningful

Comparisons are crucial. They fill Abstracts, Results and Discussions: comparisons between groups, between theory and observation, between your study and others, and so on. With well-written comparisons, you demonstrate the clarity and logic of your analysis, and provide meaningful information; without good comparisons, your data lack meaning.

The example of an unclear comparison that I'm going to use comes from the abstract of a published, peer-reviewed paper. Because I don't want to embarrass the author, I've changed or omitted certain details, including the species, so this example does not present a real scientific finding. However, I have kept the structure of the comparison the same. 

An analysis of hematological indicators in puppies of breeds X and Y

Hematological indicators A, B, and C are used to determine the overall health status of dogs and to diagnose many diseases. The normal ranges of these indicators differ with age and sex, and recent studies also indicate that, in healthy adults of breeds X and Y, the values of these indicators can be outside what were previously considered to be the normal ranges for all dogs. However, it is not known if the levels of hematological indicators A, B, and C in healthy puppies of breeds X and Y can be outside the established norms. To answer this question, [...samples were taken from certain groups at certain times, etc.]. We found that, especially during the 2nd and 3rd months of life, the mean level of hematological indicator A was significantly higher in breed X (P < 0.05). [more details, which do not explain this comparison] 

Problem 1:
Higher than what? Higher than the established norms, than at birth, than in breed Y? The unknown and the research question suggest that the writer means "higher than the established norms", but we need to be sure. 

Solution:
Write complete comparisons: not "this was higher," but "this was higher than that." 

Problem 2: 
How much higher? Let's assume that the author is using "significantly" in the correct scientific sense, to indicate a "statistically significant" difference, not a "large" or "important" difference (Hofmann 2014). So we know that there probably is a real difference between the mean level of indicator A in breed X and whatever the author was comparing it to. But we don't know if this is a big or important difference. What if the difference is so small that it will be difficult to detect with the equipment that most veterinarians have? A "negative result" like this is still valuable, and the tendency not to publish negative results from medical studies is unscientific, unethical, and dangerous (Evans et al. 2011), but the result needs to be made clear. 

Solution: 
Remember, your readers need to know the size of the effect or the difference, not just that there probably is an effect or a difference (Evans et al. 2011, Nuzzo 2014). Be precise, and include information on both the size and the statistical significance, for example: 

"Although the difference was significant, the mean level of hematological indicator A was only slightly higher in breed X at 4 weeks of age than at 2 weeks of age (4 weeks [mean, standard deviation], 2 weeks [mean, standard deviation], P < 0.05)."  

Conclusion: 

Before you submit your paper, check it for these kinds of errors. It's easy to forget and write an incomplete or unclear comparison, and I've done it many times myself—in fact, a student found one in my writing just this Friday! 

References:  
Evans I, Thornton H, Chalmers I, Glaszou P. 2011. Testing Treatments: Better Research for Better Healthcare. Pinter & Martin, Ltd: London. p.88–89, 96–7, 163.
Hofmann, AH. 2014. Scientific Writing and Communication: Papers, Proposals, and Presentations. Oxford: Oxford University Press. p. 17, 270.
Nuzzo R. 2014. Statistical Errors: P values, the 'gold standard' of statistical validity, are not as reliable as many scientists assume. Nature 506:150-152.

Better Ways to Graphically Present Your Data

Here's the title and the abstract from an article that shows you how to make your figures "worth a thousand words" (emphasis added):

Beyond Bar and Line Graphs: Time for a New Data Presentation Paradigm

Figures in scientific publications are critically important because they often show the data supporting key findings. Our systematic review of research articles published in top physiology journals (n = 703) suggests that, as scientists, we urgently need to change our practices for presenting continuous data in small sample size studies. Papers rarely included scatterplots, box plots, and histograms that allow readers to critically evaluate continuous data. Most papers presented continuous data in bar and line graphs. This is problematic, as many different data distributions can lead to the same bar or line graph. The full data may suggest different conclusions from the summary statistics. We recommend training investigators in data presentation, encouraging a more complete presentation of data, and changing journal editorial policies. Investigators can quickly make univariate scatterplots for small sample size studies using our Excel templates.

The authors not only provide Excel templates, but also instructions for how to make better figures with GraphPad PRISM. I hope you find them useful.

Reference

Weissgerber TL, Milic NM, Winham SJ, Garovic VD (2015) Beyond Bar and Line Graphs: Time for a New Data Presentation Paradigm. PLoS Biol 13(4): e1002128. doi:10.1371/journal.pbio.1002128

Is it hard for you to communicate in English? Good, you can win $500.

I'd love to see a scientist who's an English-language learner win one of these awards from PLOS (emphasis added):

"PLOS is offering up to ten travel awards to early career researchers to communicate their work at an upcoming conference. To be eligible researchers must have published with PLOS, be presenting work at a scientific conference, and currently be part of a graduate program or have received a graduate degree within the last five years.

"If you are an early career researcher, we invite you to share your thoughts on what is the biggest hindrance for communicating science and what you or your peers can do to address this issue. Apply for a chance to win $500 to offset travel expenses associated with presenting work at a scientific conference taking place between August – December 2015.

"The deadline for submission is June 30, 2015."

Vocabulary

• To be eligible means to be allowed to enter the competition.
• A hindrance for communicating is something that prevents or stops you from communicating your science.
• When they write that they will offset travel expenses, they mean that they will pay you the $500 after you show them proof that you've been at the conference.

I encourage you to go to the official PLOS blog for more details. Let them know how much harder you have to work because you're learning English, e.g. the extra time you need for writing. Good luck!

A Lesson from a Nobel-Prize Winner: How to tell the story of your results

Many scientists don’t realize it, but a good scientific article is like a novel: they both tell a story [1]. A well-written research article tells us about the search for the answer to a question. When we read the article, we’re introduced to what is known and unknown, which leads us to the research question. Then we follow the action of the Methods and Results, until we reach the climax: the answer to the question. The story finishes with a Discussion of what the answer means, which usually suggests new questions for new heroes (other scientists) to pursue—and these heroes don’t reward the story-teller with gold, but with citations!

One of the great heroes of science, Nobel Prize Winner Shinya Yamanaka, and his colleague, Kazutoshi Takahashi, give a master class in scientific storytelling in an article [2] that was a key to Yamanaka’s Nobel Prize. (If you want to download the article so that you can read the whole thing, you can get it for free from Cell’s open archive.)

How can I quickly check if a word or phrase is correct scientific English?

You try to write your papers clearly, precisely and correctly. You go to English lessons; you regularly read articles from well-edited journals* — not just for the science but for the language too. But sometimes you’re not sure what’s correct and you need the right word or phrase immediately. So what can you do?

Here’s a way you can quickly search well-edited journals to find the correct word or phrase. In this example, let’s imagine that you’re not sure if “ultrasound disintegration” or “ultrasonic disintegration” is correct.

Keep This Book In A Safe Place! A review of "Eloquent Science"

For my work as a teacher of scientific English, I have a shelf full of textbooks, manuals, and references. But one book is never there when I need it: "Eloquent Science" (Schultz 2009). This is because my wife takes it. Without asking.

Yes, even though Ania’s first language is Polish, and the book is in English, she takes it. And, even though she’s a veterinary scientist, and the subtitle of the book is “A practical guide to becoming a better writer, speaker and atmospheric scientist”, she leaves it on her desk or in her bag. Without telling me where it is, of course.

So I went to my wife and said, “Why are you always stealing my book?”

Things got exciting. Anyway, after a serious talk about how married couples share (I nodded), we got to the part you want to hear about. Ania told me that Schultz covers all aspects of writing research articles, plus posters, presentations and how to write reviews of other scientist’s papers. He writes clearly and briefly, with many lists and tables, so you don’t have to spend unnecessary time reading.

Are you using your favorite word incorrectly? (Other misuses of “parameter”)

The word parameter has been corrupted. Originally, it was just a mathematical term, but now it’s used in a vague way by the general public (Burchfield 2000, 570). Politicians and journalists love to talk about “the parameters of a situation” — it sounds so scientific! However, even a basic introduction to statistics for people who are afraid of mathematics will warn you that this is not the correct technical usage of the word (Rowntree 2000, 83).

Unfortunately, imprecise usage of the word parameter has infected the scientific world. In my last post, I explained what a parameter is and how it's different from a variable. But parameter is also confused with other words. For example, after reading that post, Mariusz Kowalewski of the University of Zurich emailed me that he often sees people writing parameter when they mean factor. (Thanks, Mariusz, for pointing this out.)