pymare.datasets.michael2013

michael2013()

Load a dataset of studies on the persuasive power of a brain image.

This dataset was published in Michael et al.[1], and was curated in metadat [2].

Returns:

• df (DataFrame) – A dataframe with the following columns:

  • "Study": the study name

  • "No_brain_n": the sample size for no-brain-image condition

  • "No_brain_m": mean agreement rating for no-brain-image condition

  • "No_brain_s": standard deviation of agreement rating for no-brain-image condition

  • "Brain_n": the sample size for brain-image condition

  • "Brain_m": mean agreement rating for brain-image condition

  • "Brain_s": standard deviation of agreement rating for brain-image condition

  • "Included_Critique": whether a critique was included in the study or not

  • "Medium": the medium of the study

  • "Compensation": notes on the compensation of the study

  • "Participant_Pool": notes on where participants were recruited

  • "yi": Raw mean difference, calculated as Brain_m - No_brain_m

  • "vi": Corresponding sampling variance

• metadata (dict) – A dictionary with metadata about the columns in the dataset.

Notes

For more information about this dataset, see metadat’s documentation: https://wviechtb.github.io/metadat/reference/dat.michael2013.html

References

[1]

Robert B Michael, Eryn J Newman, Matti Vuorre, Geoff Cumming, and Maryanne Garry. On the (non) persuasive power of a brain image. Psychonomic bulletin & review, 20(4):720–725, 2013. URL: https://doi.org/10.3758/s13423-013-0391-6, doi:10.3758/s13423-013-0391-6.

[2]

Thomas White, Daniel Noble, Alistair Senior, W. Kyle Hamilton, and Wolfgang Viechtbauer. metadat: Meta-Analysis Datasets. 2022. R package version 1.2-0. URL: https://CRAN.R-project.org/package=metadat.

Examples using pymare.datasets.michael2013

The Basics of Running a Meta-Analysis

The Basics of Running a Meta-Analysis