The quantitative research study I selected for this week was by Haggard et al. (2019), that focused on the supraliminal and subliminal religious priming and how it increased benevolent sexism. The purpose of this study was to fill the gap left by many previous studies that mainly focused on a correlation between religion and sexism, without going deeper to look at how religious priming impacts sexism. Four different methods were used to collect data, from different countries, with participants being Catholic, atheist and/or theist. The four different studies looked at religious priming impacted sexism (Haggard et al., 2019, p. 393).
As Dietz & Kalof (2009, p. 4) explain, a model has the form of Y = f(X) + E, where the dependent variable is Y, the independent variable is X and E is the error. Using this model, for the study by Haggard et al. (2019), the dependent variable (Y) would be sexism, and the independent variable (X) would be religious priming. Everything else that would impact the dependent variable would be an error (Dietz & Kalof, 2009, p. 12), which is represented by E. There must always be the assumption in research that the model will contain error (Dietz & Kalof, 2009, p. 21). In the case of the study by Haggard et al. (2019), anything other than the religious priming that impacts sexism would be an error.
Some of the errors that would have occurred are sampling error, because they may not speak for the rest of the population. Haggard et al. (2019, p. 396), state that they cannot confirm the “…participants’ true level of awareness of the primes in each of studies, though those who explicitly reported awareness of the primes or their potential impact were removed from further investigation in all cases…”. Measurement error is another type of error that could occur because as Dietz & Kalof (2009, p. 17) mention, that most variables being studied will involve some mismeasurement. This goes back to the earlier discussion where Haggard et al. (2019, p. 396) could not confirm all participants level of awareness to priming, and the differences in level of understanding could cause measurement error and skew results.
Dietz, T., & Kalof, L. (2009). Introduction to social statistics: The logic of statistical reasoning. West Sussex, United Kingdom: Wiley-Blackwell.
Haggard, M. C., Kaelen, R., Saroglou, V., Klein, O., & Rowatt, W. C. (2019). Religion’s
role in the illusion of gender equality: Supraliminal and subliminal religious priming increases benevolent sexism. Psychology of Religion and Spirituality, 11(4), 392–398. https://doi-org.ezp.waldenulibrary.org/10.1037/rel0000196