Human Cooperation Databank

Overview of the studies

Show studies by

Country/Region Year of data collection Sample size

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Select studies

Choose inclusion criteria to select studies.

Use one of our selection examples:

*Please allow some time for the data to update.

Or make your own selection:

Trial of cooperation

Overall proportion of cooperation

Overall mean of contributions

Overall mean of withdrawals

Overall standard deviation of contributions or withdrawals

Percentage of endowment contributed

Number of observations

Explore your selection

Click on the rows in the table to de-select effect sizes

APA references (.rtf)

Bibtex references (.bib)

Raw dataset (.csv)

Meta-analytic models

In order to do this, you need to select some data first.

Go back to data overview and select at least one specific IV Treatment.

Choose your model

Choose an effect measure:

Specify a model

Moderators

Choose additional moderators (mods.) for your analysis

Variable mods.

Study mods.:

Multilevel clusters:

Country/Region mods.

Calculate sample size based on effect size, significance and power.

Choose a test family:

test type:

In a funnel plot, effect sizes are plotted against their corresponding standard errors. In the absence of publication bias, studies with high effect size will be plotted near the average, and studies with low precision will be spread evenly on both sides of the average, creating a roughly funnel-shaped distribution. Asymmetry in the shape can indicate publication bias.

source: https://en.wikipedia.org/wiki/Funnel_plot

Trim&Fill

Raw output

Choose one moderator:

Show studies by

Forest Plot Violin Plot

A violin plot is a method of plotting effect sizes, with the addition of the probability density of the data at different values, usually smoothed by a kernel density estimator. Typically a violin plot will include a marker for the median of the data; a box or marker indicating the interquartile range; and possibly all sample points, if the number of samples is not too high.

source: https://en.wikipedia.org/wiki/Violin_plot

A forest plot graphically displays effect sizes from a number of scientific studies addressing the same question, along with the overall results.

source: https://en.wikipedia.org/wiki/Forest_plot

Raw output

Analyze citations

The network below shows papers and their citations. Larger nodes are more highly cited papers.

To improve visualization performance, we only display papers from CoDa that are cited at least 2 times. For a static version including all citations, click here .

Color network by:

Paper Year

remove edges

Ontology overview

Explore the ontology of Independent Variables

The image shows all the Independent Variables (IV) that were used to annotate studies and their treatments. The size of the bubbles indicate how many treatment were annotated with the IV. Click on a chosen circle to zoom in and see the subclasses, and click on the external circles to zoom out. For a more specific description of the IVs, you can refer to the table below.

Independent Variables details

Below a description of the independent variables, their moderators, and their possible values. For further details, see also https://data.cooperationdatabank.org/ .