ESRA 2027 sessions by theme

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Session Details

Reliable data on LGBTI+ populations are essential for understanding inequalities, monitoring social change, and informing effective policies. Yet, collecting and analysing data on LGBTI+ populations remains particularly challenging. Existing data collections often fail to capture the diversity and complexity of LGBTI+ experiences, resulting in important evidence gaps that can limit the effectiveness of policies and interventions and ultimately affect the lives and well-being of LGBTI+ people.

LGBTI+ populations may be considered hard-to-reach populations, requiring carefully designed sampling and recruitment strategies to achieve adequate coverage and representation. At the same time, data collection and analysis raise specific methodological and ethical challenges related to confidentiality, privacy, disclosure, and the protection of participants. These challenges are becoming increasingly important in a context in which LGBTI+ data collections may face new and emerging threats, including political and institutional resistance to collecting information on sexual orientation and gender identity, restrictions on the availability or use of such data, concerns about data misuse and re-identification, and growing pressures to limit the visibility of LGBTI+ populations in official statistics and research.

Methodological challenges also arise at the analysis stage. Concerns about disclosure and stigma may result in measurement error, including underreporting of discrimination, victimisation, or other sensitive experiences. Moreover, the distributions of some outcomes may be characterised by substantial zero inflation or sparse observations, making conventional statistical approaches inadequate and requiring innovative modelling strategies.

This session invites substantive and methodological contributions addressing challenges in the collection, integration, and analysis of data on LGBTI+ populations. Contributions may address sampling and recruitment designs, questionnaire and measurement issues, confidentiality and privacy, threats to LGBTI+ data collection, data integration and new forms of data, weighting and adjustment approaches, and statistical modelling strategies for producing robust and representative evidence.