106 analyst-team effect-size estimates of the relation between religiosity and well-being from Hoogeveen et al. (2023)

The data set contains standardized effect-size estimates, standard errors, 95% confidence interval bounds, sample sizes, effect-size types, sequential analyst-team identifiers, and team-level characteristics describing psychological dependent-variable coding and self-reported methodological knowledge. The Many-Analysts Religion Project examined whether religious people self-report greater well-being (Hoogeveen et al. 2023) .

Usage

Hoogeveen2023

Format

A data.frame with 9 columns and 106 observations:

yi

Standardized effect-size estimate.

sei

Standard error of the effect-size estimate.

lci

Lower bound of the reported 95% confidence interval.

uci

Upper bound of the reported 95% confidence interval.

ni

Analysis sample size.

type

Reported effect-size type: standardized regression coefficient beta or Cohen's d.

team

Sequential analyst-team identifier in this example.

team_psych

Whether the effect estimate used the psychological dependent-variable coding.

team_knowledge

Team's self-reported methodological-knowledge rating, from 1 (no knowledge) to 5 (expert).

Source

https://osf.io/gkxqy/

References

Hoogeveen S, Sarafoglou A, Aczel B, Aditya Y, Alayan AJ, others (2023). “A many-analysts approach to the relation between religiosity and well-being.” Religion, Brain & Behavior, 13(3), 237–283. doi:10.1080/2153599X.2022.2070255 .