Conflict of interest in social science

There is one great thing about medical and epidemiological research – declaration of the conflicts of interest.  Medical researchers, usually before they actually present any research results, declare that they are not biased by financing or obligations to pharmaceutical companies, to producers of devices, commercially promoted ways of treatment, or anything like this.

However, social scientists do not bother with such nuance. Not-so-smart ones would claim they try to be objective. Smart ones would say: “Of course we’re biased”, but would never reflect in their articles in which way (and editors would not accept such papers). Given the neo-positivist ethos of the leading journals in sociology and social psychology, conflict of interest  (or researcher’s personal bias) can undermine many conclusions without even acknowledging it. Especially when a researcher has so many degrees of freedom. It looks totally outdated, as if we haven’t had all these anti- and post-positivisms, or critical theory.  Haven’t every reader thought about comparing consistent results of some prominent scholars of, for example, values and moral attitudes with their personal views? We can try to avoid this bias statistically, but we cannot easily reshape the way we think, so the least we can do is a declaration of researcher’s personal opinions added to every article. Of course, this is a very personal stuff, but I think it would greatly amend a positivist pathos of many, many articles.

“The Psychology of Human Values” by Gregory Maio

There is a great new book on the market about basic values. For academics, it’s a new point of reference after a long time (for me it was Hitlin & Piliavin, 2004). It’s also great for newbies and anyone who’s just developed their interest in basic values. It sorts things out about what values are, what they depend on, what they can influence, whether they change, or can be manipulated. Gregory Maio did a great job in summarising much of the recent studies.

The Problem of Human Values.
Section 1: Beginnings in the Empirical Study of Human Values
1. A brief history of values
2. Types of values.

Section 2: Values in Psychology
3. Connections to motives, traits, and habits
4. Connections to ideology and attitudes
5. Components of values.

Section 3: Forces that Shape Values
6. Personal influences on Values
7. Social influences on Values.

Section 4: When and how values matter
8. Effects on prejudice and well-being
9. When values matter
10. How values matter.…/…/9781841693576

Ways to do Latent Class Analysis in R

The best way to do latent class analysis is by using Mplus, or if you are interested in some very specific LCA models you may need Latent Gold. Another decent option is to use PROC LCA in SAS. All the other ways and programs might be frustrating, but are helpful if your purposes happen to coincide with the specific R package.

CRAN offers plenty of different ways to get clusters on your data, but most of these packages have a very narrow and specific utility. For example, I found at least 15 packages involving latent class models, of which only six perform latent class analysis in the form of classification based on indicators, and only two of them allow including nominal indicators, and none allows including ordinal indicators.

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“Church attendance” question in WVS-5


I’ve never noticed that note. As I figure it out, this is an attempt to overcome the widely known differences in church attendance between Muslims and Christians: Muslim women are not required to go to Mosque, whereas Christian women go to Church more frequently than Christian men (what about Buddhists?).

So basically it says that there are two different questions asked in ‘Islamic societies’ and the rest of the world, which are stored in a single variable in WVS dataset.

The use of different indicators for measuring the same construct is justified in the reflective measurement logic in which all the indicators are exchangeable, though I doubt it relates to a single-indicator measures.

I  checked questionnaire translations in “Islamic societies”, as it seemed to me too strange. What I found is  even more surprising. Summing up, the question about praying  only Morocco and Malaysia unambiguously asked about praying (though some troubles with options coding in Malaysia). The rest seven translations were either about attending mosques or ambiguous. Find below the detailed report. Thus, in general, we can quietly ignore The Note, just like the questionnaire translators did.

To be serious –  when using WVS or some other comparative survey data, every single question should be analyzed in (at least) the way I did it below, especially for your key variables and absolutely necessary for your dependent variables. Google is a handy tool, it gives a crude translation but you get a general idea of what’s in the question. You’ll find plenty of interesting surprises.

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Social networks data collection tools

Collecting social networks data with R is highly beneficial since it can update results/graphs/reports on the air.

Here are the basic ones:

All of them are based on the functions provided by httr or RCurl and work mostly using GET and POST web requests dealing directly with a corresponding network’s API. This is not too hard to develop your own tool for your specialized purposes, it will only take some time to get acquainted with specifics of your network’s API (which is usually quite simple). There are tools that  integrate these packages with graphing and network analysis tools, such as SocialMediaLab.

Christian Welzel addresses my criticism

The following is Christian Welzel’s response he kindly provided following the post in which I summarized my criticism of his and Ronald Inglehart’s paper on measurement invariance:

This dismissive portrayal of our contribution does not come as a surprise. Indeed, no one who considers “internal coherence” as the prime criterion of measurement quality can be happy about our article. But that does not make the uncomfortable truth less true: the logic of internal coherence often prompts scholars to disqualify a multi-item construct as invalid, despite the fact that this very construct shows meaningful, important and powerful “external linkages” with its expected correlates. Scholars who advocate internal coherence as the gold standard of measurement quality offer no explanation of why weak internal coherence coexists so easily with strong external linkages. In fact, most of these scholars do not even address this phenomenon. Or they play it down, as if external linkages had nothing to do with a construct’s reality anchorage.

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Is measurement invariance just a nonsense?

The short answer is No.

But Christian Welzel has a different opinion. He and Ronald Inglehart have challenged the very common and largely accepted though sometimes tedious and uncomfortable practice of measurement invariance testing. I do not agree with them but their challenge provokes a lot of thoughts and clarifications in a current paradigm.

Aleman and Woods (2015) were one of the few researchers who attempted to check Self-expression values index for measurement invariance across countries. Earlier, Hermann Dulmer and myself were trying to do more or less the same. I simply didn’t have my MGCFA models converged, there was too much non-invariance.

Christian Welzel and Ronald Inglehart do not think that these tests make any sense. Continue reading