Estimation of Impact Factors

Scientific excellence is often burned down to some numbers. For academics, it is publish or perish and bibliographic analysis is an important factor for academic careers. A bibliographic analysis includes how many papers somebody published, where they published, and how many citations their publications received. One of the numbers that sums up the quality of publications is the impact factor, which classifies journals and is often taken as the quality of individual publications published in those journal. There are services that calculate these impact factors, most prominently isiweb of knowledge, however they provide limited access (they are subscription based) and they only publish impact factors for journals that exist already for at least four years. Here I discuss shortly a method based on google scholar to estimate impact factors and I use it to estimate an impact factor for the journal frontiers in systems neuroscience.

What is the impact factor?

I am only paraphrasing slightly from the wikipedia article on the impact factor:

In a given year, the impact factor of a journal is the average number of citations received per paper published in that journal during the two preceding years. [...] Papers published includes citable items, which are usually articles, reviews, proceedings, or notes; not editorials or Letters-to-the-Editor.

There are alternative strategies to evaluating journal impact, such as eigenfactors, which are probably a better indicator of importance than the impact factor, however the impact factor is commonly used and cited.

Average citations

I am trying to estimate impact factor from google scholar, using the publish or perish software as search front-end.

Search for journal Frontiers in systems neuroscience between 2009 and 2010. Results from publish or perish below.

Papers: 110 Cites/paper: 4.82 h-index: 13 AWCR: 239.50
Citations: 530 Cites/author: 182.54 g-index: 16 AW-index: 15.48
Years: 3 Papers/author: 41.93 hc-index: 17 AWCRpA: 81.49
Cites/year: 176.67 Authors/paper: 3.25 hI-index: 4.02 e-index: 7.55
hI,norm: 6 hm-index: 7.98

The number we are looking for are the cites/paper: 4.82.

Discounting

The impact factor counts only citations received during the year after the publication period. Therefore, we should discount for citations during that time. This is not easily possible in google scholar. Therefore, because citation patterns over time should be similar over journals within a scientific domain, I suggest to discount by a factor suggested by other journals for which the impact factor is known. Probably the citations follow a log-curve over time, however a scalar discount factor could suffice for our purpose.

I will now calculate a discount factor based on impact and citation data for two journals, Neuron and PLOS Biology.

According to google scholar, papers in neuron published during 2009-2010 received an average of 20.25 citations since publication. Neuron's impact factor according to Isiweb is 14.027. Therefore, the discount factor should be 14.027/20.25 is roughly 0.69.

For PLOS Biology (impact factor 12.472) the average citations since publication for papers during the period 2009-2010 is 23.755. The discount factor should therefore be 12.472/23.755, roughly 0.52.

The higher discount factor for Neuron could mean that articles in PLOS Biology have a shorter half-life (i.e. Neuron articles get cited for longer periods of time).

Estimated impact factors

For the journal Frontiers in Systems Neuroscience, discounted according to the model by PLOS Biology, the estimated impact factor would be 4.82*0.52, roughly 2.51. According to the Neuron discount factor, the estimated impact factor would be 3.33.

I tried this out with other journals. For the journal of neuroscience, publish and perish's limit of 1000 papers was reached, so the estimate (11.04) is skewed by publications with higher impact that come first in search results. Maybe introduction of some arbitrary search queries could help, but I am moving on to other journals. For Plos Genetics I got "Cites/paper: 12.15" which would be 6.44 and 8.38 discounted, respectively, while the impact factor of 2010 is 9.543.

The the journal of computational neuroscience reports an impact factor of 2.325 on its web page, while I get 4.43 cites/paper, which would be discounted to 2.35. Frontiers in computational neuroscience has an impact factor (as of 2010) of 2.586 and I find 3.13 cites/paper from google scholar; discounted this would amount to 1.66 and 2.16, respectively.

So the estimate from google scholar is sometimes very crude, but maybe indicative for similar journals.

Conclusions

As indicated before, this estimation has to be taken with a grain of salt. Google scholar results are ordered by pagerank, so you have to take care not to loose the less-cited paper in the analysis. Important in this context is that frontiers in very well-indexed (DOAJ, CrossRef, PubMed Central and PubMed, Google Scholar, SCOPUS) which means that no papers get lost, otherwise we might loose papers that are not indexed or not cited. This could mean that estimates for frontiers journals from google scholar are better than for other journals that are not as well-indexed.

Google scholar takes into account a very broad spectrum of journals and many conferences. Isiweb impact factor includes only citations from journals. It also excludes self-citations, however self-citations (as I found in some study) do not co-vary (at least not significantly) with the number of citations of a paper (which means self-citations do not distort results if you compare different results at least).

Please leave a comment below for questions and suggestions. [ Read more... ]

Handwashing Behavior - Or: Should I take the Peanuts?

Minuscule particles between dermal ridges in the hand, hardly seen by the naked eye. via wikipediaI don't think I am obsessed with personal hygiene, although, I am averse to certain behaviors, such as when you pick your nose next to me and then flip your snot in my direction, or when you reach out to touch me after having been touching dirty things on the street. What sometimes sets me off is seeing people exit the bathroom without washing their hands. I was also surprised, that when toilets featured shared faucets, to see this frequently with women (or should I say rather, not to see it). Now what about the peanuts in the bar? The guy, who just grabbed 10 more peanuts than his hand could hold and let half of them fall back into the bowl, what did he touch before? Should you really eat any of the peanuts? How many people wash their hands anyways?

In 1847 Ignaz Semmelweis showed that hand washing of midwives helped to reduce significantly mortality rate of childbed fever, from aroud 10 percent to around 1 percent, although at the time, he became rather unpopular for it. In 1890, Robert Koch demonstrated that anthrax was caused by the bacterium Bacillus anthracis and provided evidence for Pasteur's germ theory. Despite the implications for hygiene being so clear, it is again a case of theory against practice as case studies show.

Results from studies on hand washing behavior vary, debited in part to experimental protocol. Amanda Stinson concluded in her article "Hand washing behavior of women in public bathrooms", that due to an increased self-awareness, subjects were more likely to wash their hands when someone else was present washing their hands. Stinson distinguished between three conditions in her study on hand washing behavior of women:

1. No observer was visible
   
2. A person is talking on the cell phone next to the faucet
   
3. A person is washing her hands

She found that overall only 40 percent of young women washed their hands. In the hand washing condition (3), the subjects were more likely to wash their hands, 56 percent, while in the cell phone condition (2), subjects were less likely to wash their hands 27 percent. Stinson also found a strong and highly significant negative correlation between the time of night and whether or not the subject washed her hands.

In some studies it is not very clear whether the social factor mentioned above was taken into account so it is difficult to compare data over different studies. It also becomes clear from another study (see below), that age and education could be correlated variables. I therefore mention only one more study to compare men and women's hand washing behavior.

In the study "Gender and ethnic differences in hand hygiene practices among college students" by Anderson and colleagues it is not completely clear how they observe people in restrooms, however they make no mention of controlling the social variable and I would speculate that the difference from the results above could be explained in terms of social pressure.

What they found is that men washed their hands in 38 percent of cases and women in 62 percent,hand hygiene in females would be better than in males. In the discussion, Anderson and colleagues reference earlier similar evidence. They provide the argument that females' higher compliance could be associated with their tendency to practice socially acceptable behaviors. This however would also mean that having somebody watch you in the bathroom would have a stronger effect on women than on men, so that the question of who is more hygienic, men or women, cannot be answered conclusively.

Interestingly, Anderson and colleagues found that the minority students exhibited better hand hygiene practices than the Caucasian students. Comparing other studies they find that hand washing behavior in this college student population was only slightly higher than in populations of middle school and high school students. As for adequacy of hygiene, they report that only a small proportion of those who washed their hands did so for 20 seconds.

To come back to the original question: should I take the peanuts? I think that's a question of priority: just how hungry are you?

Enjoy those peanuts. At least as long as you can. Please leave a comment below for questions and suggestions. If you liked this article you might also want to read about the speed of nail growth. [ Read more... ]

Atheism around the World

The rate of atheism or agnosticism in different countries is a question which can commonly sneak up in discussions over dinner or lunch. Atheist writers, such as Richard Dawkins and Christopher Hitchens, argued that belief in "a bearded man in the sky" — to take a somewhat provocative verbal expression — interferes with perception of reality.

While there are few people who would go as far as to actually claim that rate of religious belief is inversely proportional to national intelligence (see below), some people may take a high rate of believers as a measure of backwardness. Intuitively, I would guess it is probably relatively safe to claim that atheism rate is indicative of education level and economic well-being. I found a map of atheism worldwide, which I show, I outline the argument around atheism, and give a short discussion.

The data in the map come from different sources and are subject to different sorts of methodological differences and should therefore be taken with a grain of salt. Please, click on the link for a list of sources and to get a bigger image.



In many developed countries, people go to church on at least four occasions baptism, confirmation, wedding(s), and funeral(s). Some time ago, I wrote an article about belief in evolution worldwide, with a graph included that looked quite similar to this one.

I promised a discussion of the argument that religious belief is a sign of backwardness, so here it comes.

Is National IQ Related to Atheism Rate?

Richard Lynn, one of the discoverers of the Flynn effect, published together with others the study "Average intelligence predicts atheism rates across 137 nations." In it, after reviewing previous supportive studies, the authors find further evidence for significant negative correlation of IQ and religious belief within nations.

So, there you have it.

However, then the problems begin and I have to take this detour to distance myself from other results of this study.

They then go on to correlate national atheism rates with national IQs as Lynn previously had compiled in a book, mostly based on Pisa international education assessment studies and find again a negative correlation of educational success and religious belief over populations of different countries.

Rather than arguing for a correlation of education with atheism, the authors argue for a correlation of national IQ and atheism rate, which is not unproblematic. The main problem are methodological confounds about how to define/calculate national intelligence. They include factors of economic development (see below). Further, the authors argue backwards, saying basically that people are religious and uneducated because they are stupid (genetically).

The Flynn Effect and Atheism

It is worth to point out at this point that Lynn's claim to fame beside the Flynn effect is his quest to find racially conditioned differences in intelligence. I am therefore making a detour to point out the confusion of concepts and because I don't feel comfortable in citing a study by Lynn without qualification. Lynn states on his departmental web page:

In 1991 I extended my work on race differences in intelligence to other races. I concluded that the average IQ of blacks in sub-Saharan Africa is approximately 70. It has long been known that the average IQ of blacks in the United States is approximately 85. The explanation for the higher IQ of American blacks is that they have about 25 per cent of Caucasian genes and a better environment.

An abstract of one of his papers, Sex differences in intelligence and brain size is no less controversial: A paradox resolved, reads:

Males have larger brains than females, even when corrected for body size, and brain size is positively correlated with intelligence. This leads to the expectation that males should have higher average levels of intelligence than females. Yet the consensus view is that there is no sex difference in general intelligence. An examination of the literature shows that the consensus view is wrong. Among adults, males have slightly higher verbal and reasoning abilities than females and a more pronounced superiority on spatial abilities. If the three abilities are combined to form general intelligence, the mean for males is 4 IQ points higher than the mean for females. Among children up to the age of around 14 yr the sex differences are smaller because girls mature earlier than boys. The evolutionary selection pressures responsible for greater intelligence in males are discussed.

The article "Why national IQs do not support evolutionary theories of intelligence" delivers rebuttals for most of the claims (emphasis is mine):

We show that these studies assume that the Flynn Effect is either nonexistent or invariant with respect to different regions of the world, that there have been no migrations and climatic changes over the course of evolution, and that there have been no trends over the last century in indicators of reproductive strategies (e.g., declines in fertility and infant mortality). In addition, we show that national IQs are strongly confounded with the current developmental status of countries. National IQs correlate with all the variables that have been suggested to have caused the Flynn Effect in the developed world.

In fact, in the book mentioned above, Lynn and his co-author, Vanhanen, find correlations between the national IQ, as they calculate it, and many other factors. The human condition index (QHC), which they derive in the book, is found to be very highly correlated with national IQs. The QHC is composed of the following:

1. purchasing power parity Gross National Income (PPP-GNI) per capita 2002
   
2. adult literacy rate 2002
   
3. gross tertiary enrollment ratio
   
4. life expectancy at birth 2002
   
5. the level of democratization 2002.
   

One of these factors is education, which they use to calculate their IQ scores, so a high correlation is not too surprising. Basically the whole argument of national IQs boils down to saying religious belief correlates negatively with factors such as purchasing power parity, literacy rate, education, life expectancy, and others. I find it both ironic and sad, that Lynn forgets about the effect he helped to discover.

Concluding, religious belief (or rather the absence) seems to be one of the indicators of development.
[ Read more... ]

Sleep Patterns as a Function of Age

Sleep is not the same over a human life time. The time to fall asleep, the efficiency of sleep, and the amount of sleep vary with age. I found a great article about age-related changes in sleep patterns and thought it is of general interest to show some of the graphs that show these changes. It also shows that there is a difference between depressed and normal people. Read on to see them.

I found this in an article called "Age-related changes in sleep in depressed and normal subjects" by Gillin and colleagues published in the journal Psychiatry Research (vol 4, nr. 1) in 1981. They did all-night electroencephalography during sleep of people diagnosed with depression (78 people in total) and controls (who were not diagnosed as depressed, 36 in total). Both groups of people were unmedicated.

They found that healthy (non-depressed) people sleep more than depressed people.


Interestingly the total sleep time of sleep decreases over age. This trend is very much pronounced in depressed people. Another chart shows that the REM latency (the time to reach REM sleep) decreases over time, so people over age, become better with age in reaching REM sleep.

They also found that depressed people took longer to fall asleep as evidenced in the graph below.


From looking at the other charts, the time to wake up seemed to be inversely correlated on the latency (time to fall asleep) and of sleep duration. Depressed people took much longer to wake up. Depressed people not only sleep less, but also they wake up more frequently during the night.

(Please note, that the colors are inverted for depressed and healthy people (between the two graphs.)

Enjoy. Please leave a comment below for questions and suggestions. [ Read more... ]