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Introduction to Lab²: A MetaLab for Better Science

The replicability crisis highlights the need for more transparent and robust research practices. Lab² (Lab-Square) is a collaborative initiative using meta-scientific approaches to improve research credibility. Through large-scale projects like Many-Labs, Many-Designs, and Many-Analysts, we assess the generalizability of findings across populations, methods, and analytical approaches. Lab² also...

Learn to use the SOEP over lunch

The German Socio-Economic Panel Study is a representative panel study for the German population, collecting data on a broad variety of topics of everyday life, including general well-being, household composition, educational aspirations and educational status, income and occupational biographies, leisure time activities, housing, health, political orientation and more. With its long running panel...

Fieldwork Monitoring in Practice: Insights from 17 Large-scale Social Science Surveys in Germany

This study provides a synopsis of the current fieldwork monitoring practices of large-scale surveys in Germany. Based on the results of a standardized questionnaire, the study summarizes fieldwork monitoring indicators used and fieldwork measures carried out by 17 large-scale social sciences surveys in Germany. Our descriptive results reveal that a common set of fieldwork indicators and measures exist ...

Do talk money – Reducing income nonresponse in surveys (with Katharina Allinger)

Item nonresponse is a common issue in surveys. We implement an experiment to reduce nonresponse to income questions in an international household survey, looking at four different countries. Survey respondents are asked to report their exact household income. We randomize those who refuse to answer into two groups. In a follow-up question, the control group is asked to choose their income from a...

Special: Pre-launch presentation of SOEP Statistics – a new tool to facilitate access to weighted SOEP analyses for researchers and a broader audiencehler)

In this special Brownbag Session, we will present the platform SOEP Statistics to receive feedback from the SOEP team before we go into a final pre-launch phase. SOEP Statistics is both a data explorer and a tool to export weighted descriptive statistics of pre-screened longitudinal variables on all SOEP topics. The platform allows users to group data according to a pre-defined selection of...

The Performance of Multiple Imputation in Social Surveys with Missing Data from Planned Missingness and Item Nonresponse

Designs using planned missingness, such as the split questionnaire design, are becoming more and more important in social survey research. To ensure an acceptable questionnaire length, these approaches typically entail large amounts of planned missing data, which can be imputed after data collection. However, social surveys typically also include other types of missingness such as item nonresponse ...

Avoiding Unintentionally Correlated Shocks in Procy Vector Autoregressive Analysis

The shocks in structural vector autoregressive (VAR) analysis are typically assumed to be instantaneously uncorrelated. This condition may easily be violated in proxy VAR models if more than one shock is identified by a proxy variable. Correlated shocks may be obtained even if the proxies are uncorrelated and satisfy the usual relevance and exogeneity conditions individually. Examples from the recent ...

Learn to use the SOEP over lunch

The German Socio-Economic Panel Study is a representative panel study for the German population, collecting data on a broad variety of topics of everyday life, including general well-being, household composition, educational aspirations and educational status, income and occupational biographies, leisure time activities, housing, health, political orientation and more. With its long running panel...

SOEP Annual Report 2023

Validating an Index of Selection Bias for Proportions in Non-probability Samples

Fast online surveys without sampling frames are becoming increasingly important in survey research. Their recruitment methods result in non-probability samples. As the mechanism of data generation is always unknown in such samples, the problem of non-ignorability arises making vgeneralisation of calculated statistics to the population of interest highly questionable. Sensitivity analyses provide a ...