[Home]   PSY 101    [Psychology Images] Class 19: Research II: Looking for Links; Evaluating Research-Flaws, Placebo
Last updated: October 7, 2025

Looking For Links: Descriptive or Correlational Research

Descriptive or Correlational research can tell us if there is a link between variables, but not about cause and effect relationships

Vaccination vs. Presidential Voting 2021
Vaccination & Death Rates vs. Trump Vote

The data are clear. Yes, they are related. People living in areas where voters went for Trump in the 2020 election were significantly less likely to be vaccinated against COVID-19 AND significantly more likely to die of COVID-19 than people living in areas where voters went for Biden.


Does this mean that somehow Trump CAUSED the lower vaccination rates? Or, conversely, did the higher death rates somehow CAUSE people to vote for Trump rather than Biden? Perhaps, but we cannot say so on the basis of this evidence. They simply show that there is some sort of relationship or link.

More recent research (Reimer et al. 2022) proposes that there are other factors which are linked to voting patterns and/or vaccination/death rates. For example,
MFT-Conservatism

As you can see in the maps above of the 3000+ counties of the US, different regions of the United States are marked by differences in people's basic moral intuitions or beliefs according to Moral Foundations Theory (MFT) which, in turn, affect how people tend to behave. And, no surprise, there are clear political differences in the nation of areas that are more or less conservative politically (the more yellow areas above are more conservative and the purple areas are more liberal).

Using MFT, researchers have uncovered a set of links between various basic moral beliefs and the likelihood of vaccination or dying from COVID-19 (Reimer et al. 2022)

  • Basic moral intuitions or beliefs in the importance of "PURITY" [that is, "physical and spiritual cleanliness, self-discipline, dignity, valuing sacredness, and suppressing carnal desires" (Reimer et al. 2022, p. 754)] is related to the low vaccination/high death rates over and above political beliefs
  • Basic moral intuitions in the importance of LOYALTY ["concerns of unity, solidarity, togetherness, family, and in-group protection"]  and FAIRNESS ["concerns of equality, justice, reciprocity, and proportionality" (Reimer, p. 754)] are related to HIGHER vaccination/LOWER death rates over and above political beliefs.



How do we measure the strength of a relationship between two variables?

Correlation coefficient (= r)

[Correlation]
[Negative Correlation] {Zero Correlation] [Positive Correlation]
 Correlation (r) = -1.00   Correlation (r) = +0.05  Correlation (r) = +1.00 
* N = neuroticism, E = extraversion, O = openness to experience, A = agreeableness, C = conscientiousness
As a correlation moves from 0.0 toward +1.0 (more positive), the strength of the relationship increases. Similarly, as a correlation moves from 0.0 toward -1.0 (more negative), the strength of the relationship increases. Correlations near a value of 0.00 indicate that there is little to no relationship between two variables.

Hence, the correlation -0.90 is larger/stronger than the correlation +0.75.   The correlations of +0.63 and -0.63 are exactly the same magnitude but in opposite directions. They are equally "strong". 
Correlations say that there is a relationship, NOT that one variable CAUSES the other. It is possible that both variables are actually caused by a third or fourth variable.

NOT IN BOOK: In doing correlation research, a researcher should have a reason to suspect that a relationship between two variables might exist. In the absence of ANY plausible reason for why two variables might be related, sometimes there are data which show what are called "spurious correlations" ("spurious" means "false, not real, seemingly related but not").

One of the most widely cited examples of a spurious correlation shows almost a perfect relationship between the rate of divorce in the state of Maine between 2000 and 2009 and the per capita consumption of margarine in the U.S. in the same period.
Spurious Correlation

There is a large list of more and often very funny spurious correlations at this website.

Other forms of Descriptive Research


Flaws: Evaluating Research

Sampling Bias: Is the sample representative of the population under review?

Bias can be introduced by
Consider the infamous 1936 Literary Digest "poll" which predicted that Alf Landon would beat Franklin D. Roosevelt in the presidential election by 57% to 43% (and win a landslide 370 electoral votes!) The magazine had contacted 10 million Americans (whose names were drawn from long lists of people who owned cars or telephones). The magazine got back over 2 million responses. Of course, in the actual election, Roosevelt beat Landon by 61% of the votes (523 electoral votes vs. 8 electoral votes for Landon)
What did the Literary Digest do wrong?
See The First Measured Century (PBS): George Gallup and the Scientific Opinion Poll

Placebo Effects: Changes in a person's behavior which come from the EXPECTATION of change, rather than the ingredients or components of the treatment they receive.

Distortions in Self-Report Data: Bias introduced by participants who respond in ways that do not reflect their actual behavior, beliefs, judgments, etc.

Experimenter Bias: Bias introduced when a researcher's expectations or preferences influence the outcome of the research. This may be done without the research ever realizing that he/she is affecting the outcome.

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Looking at Ethics

Psychology studies human beings and we humans are a very complex reality to study. We are often smart enough to understand the purpose of a research study in ways that would make that study invalid. Experimenters try to get people to respond honestly, but participants might distort their responses for any number of reasons.

In the last class, I gave you an example of researching whether faculty members might have an unconscious bias against women. Notice that the participants were not told that they were being studied for bias before their responses were collected. Indeed, if you asked the participating faculty directly, they would almost certainly have denied that they had any bias whatsoever. So, the experiment disguised how bias was going to be measured by NOT telling the participants what the independent variable was, that is, the applicant was either male or female. Is such deception justifiable or ethical?

The question of deception

Animal Research

Ethical Principles in Research with Human Subjects

 
References

Downs, A.C., & Lyons, P.M. (1991). Natural observations of the links between attractiveness and initial legal judgments. Personality and Social Psychology Bulletin, 17, 541-547. https://dx.doi.org/10.1177/0146167291175009

Gunnell, J. J., & Ceci, S. J. (2010). When emotionality trumps reason: A study of individual processing style and juror bias. Behavioral Sciences and the Law, 28, 850-877. https://dx.doi.org/10.1002/bsl.939

Reimer, N. K., Atari, M., Karimi-Malekabadi, F., Trager, J., Kennedy, B., Graham, J., & Dehghani, M. (2022). Moral values predict county-level COVID-19 vaccination rates in the United States. American Psychologist, 77(6), 743–759. https://doi.org/10.1037/amp0001020


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This page originally posted on 1/28/04