Inference from Non Probability Samples
Call for Presentations

Conference of SRM, ESRA and ELIPSS
Paris Institute of Political Studies (Science PO)
March 16/17 2017

Survey Research Methods (SRM), the European Survey Research Association (ESRA) and the Étude Longitudinal par Internet Pour les Sciences Sociales (ELIPSS) seeks presentations for a conference on "Inference from Non-Probability Samples" in Paris, March 16/17 2017.

Keynote speeches will be held by Prof. Andrew Gelman, Columbia University, New York, U.S.A. and Prof. Jelke Bethlehem, Institute of Political Sciences, Leiden University, The Netherlands.

Submission and presentation guidelines


In survey research, the data collected with a survey are the facts we know, from which we want to infer certain characteristics of a defined population (descriptive inference) or about a parameter of a more general data generating process (causal inference). In probabilty samples, the process that creates the observed data from the population is well known, making descriptive inferential statements from the observed data to the population relatively unproblematic. While causal statements require further assumptions, probabiliy samples ease the inference from respondents to (classes of) human beings in general subject to assumptions being met. Probability samples have thus always been an important criterion for the quality of empirical research with surveys.

However, the role of probabilty samples for survey research have come under pressure from various directions. Unit nonresponse places a question mark on the assumption that a probabilty sample by design remains to be a probability sample in practice. In recent years, economics witnessed an experimental revolution that brought an increased use of experimental designs with highly selective research units away from the field and into computer labs, and this experimental revolution has also reached other disciplines of the social sciences. The technical innovation of web surveys has made the design of survey experiments very easy in practice although the classic distinction between internal and external validity is still a factor in judging the worth of such experiments for robust causal inference. While the response rates in classic survey modes diminish, self-selected samples of respondents are increasingly available via social networking and specialized internet platforms.

The purpose of the conference is to discuss the possibilities of drawing inferences from social science data without the use of probability samples, or from probability samples with low rates of response. What kind of research questions can be answered using self-selected samples, and what measures can be taken to combat selection bias? We seek presentations that criticize the use of non-probability samples and small-scale experiments, as well as presentations that advocate their use. Best practice examples are welcome, as well as methodological discussions.



Participants are asked to travel with their own funding. There will be a small conference fee to cover coffee and refreshments. There will be also a conference dinner at additional costs.

Scientific Organizers