Global Trust Research Consortium Fundamental Questions Are we losing faith in each other How does trust develop over the life cycle How do generations differ in trust Why are citizens in some countries more trusting than in other countries ID: 807423
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Slide1
A Mega-Analysis of Trust
Global Trust Research Consortium
Slide2Fundamental Questions
Are we losing faith in each other?
How does trust develop over the life cycle?
How do generations differ in trust?
Why are citizens in some countries more trusting than in other countries?
How does trust affect health, income, well-being?
Slide3Yet we work like…
Slide4Slide5Slide6Slide7Slide8Beta blockers
Slide9Slide10Slide11Slide12Benefits
The benefits of harmonizing and pooling research databases are numerous. Integrating harmonized data from different populations allows achieving sample sizes that could not be obtained with individual studies, improves the generalizability of results, helps ensure the validity of comparative research, encourages more efficient secondary usage of existing data, and provides opportunities for collaborative and multi-
centre
research.
Slide13Comparable projects
Luxemburg Income Study [LIS]
International
Stratification and Mobility File [
ISMF] in Sociology
Cross-national Survey Data Harmonization [SDH] Project
Durand et al. on political trust
Slide14Ex Post Survey Data Harmonization
A process:
in which
different survey datasets
that were not specifically designed to be compared
are pooled and adjusted
(i.e. recoded, rescaled, or transformed)
to create a new integrated dataset
that could be analyzed as a typical single-source dataset; and
that is based on
clear criteria
that specify which datasets are included into the new dataset and clear methods for how variables in the new dataset are created.
Dubrow
&
Tomescu-Dubrow
, 2014
Slide15Slide16Meta vs Mega-analysis
Meta-analysis also allows scholars to analyze the collective evidence on a certain phenomenon
But meta is only possible on released reports, and susceptible to publication bias
Power is limited to the #studies
Meta-analysis of Individual Patient Data (IPD) = Mega-analysis
Slide17Slide18Slide19Pp. 77-100 in: Van Lange, P.A.M.,
Rockenbach
, B., & Yamagishi, T. (Eds.). Trust in Social Dilemmas. Series in Human Cooperation, Volume 2. Oxford: Oxford University Press.
https://osf.io/umdxg/
Slide20Global Trust Research Consortium
Open Science Framework:
https://osf.io/qfv76/
Current members: René Bekkers, Arjen de Wit, Tom van der Meer, Eric Uslaner, Zhongsheng Wu, Bart Sandberg
Please join us!
You are most welcome
Slide21Surveys currently included
Multinational: ISSP, WVS, EVS, ESS, EQLS, Eurobarometer, Survey of Adult Skills (PIAAC), CID
National: German General Social Survey, BHPS /
UndSoc
Rough estimate: these surveys include about 1/3 of all trust responses ever collected
We have identified ~120 surveys since 1953 that have included variants of the trust question
Slide22Varieties of trust
Would you say… In general most people can be trusted? OR: You can’t be too careful in dealing with other people?
Forced choice format
(0 – 1)
, the Rosenberg o
riginal (1953)
With option ‘It depends’ offered
With option ‘Don’t know’ added
These poles as Likert items (1-5, 1-7, 1-10, 0-10)
Other statements about human nature (1-5)
Slide23Yay, we have variance!
We can leverage the
pecularities
of surveys as natural experiments
Use item, survey, and data quality characteristics as covariates
And add interactions with substantial correlates of trust
Slide24Predictors at 5 levels
Country
Time
Survey
Item
Individual
88
1981-2014
24
5
1,237,870
Slide25Potential Methods Effects
Question order: before / after questions that generate a ‘warm glow’
Response category format: 0-1, 1-5, 1-7, 1-10, 0-10
Mode of data collection: face-to-face, paper-and-pencil, online
Data quality: response rate, #
missings
, interviewer ratings of ‘cooperativeness’
Slide26POWER!
We should collect as many country – year observations as possible, from as many different surveys as possible
To disentangle various methods
effects
To answer questions on age, cohort and period effects on trust
To detect relationships at minuscule effect sizes
Slide27Procedure
Identify a survey not yet included
Categorize the methodology: trust measure, data collection mode
Provide code for harmonization
Add data
See results
Analyze data
Slide28Response categories
Slide29Survey mode
Note: with this n, everything is significant
Slide30Age + Cohort
Slide31And now
What would be good questions to answer?
Do you know of any surveys that we may not know of?
Would you be willing to add these surveys?
Slide32Let’s collaborate.
René Bekkers
@
renebekkers
r.bekkers@vu.nl
This project is on the Open
Science Framework,
https://osf.io/qfv76/