Students as Experimental Participants: A Defense of the "Narrow Data Base" (WP-09-05)

By James N. Druckman, Cindy D. Kam. 2009

504 citations recorded by the source corpus.

Subfields: History and Philosophy of Science, Sociology and Political Science, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/9acb2ad05b7573824c531d4a6bb1f3c91476ae85

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In History and Philosophy of Science

In Sociology and Political Science

In Statistics and Probability

Citations in the corpus

Do partisanship and politicization undermine the impact of a scientific consensus message about climate change? (2018, background): “When it comes to experimental research, such a sample is sufficient to ensure generalizable causal inferences (Druckman & Kam, 2011).”
Measuring Stereotypes of Female Politicians (2014, background): “Based on these considerations and other justifications of the usefulness of student samples (e.g., Druckman & Kam, 2011), we believe we can draw valid conclusions from this data.”
When Corrections Fail: The Persistence of Political Misperceptions (2010, unknown): “For a general defense of the use of student samples in experimental research, see Druckman and Kam (2010) .”
Influencing Climate Change Attitudes in the United States: A Systematic Review and Meta-Analysis (2020, background): “Indeed, if samples vary on important moderators of an effect (e. g., ideology), they may be prone to display differential treatment effects (Boas, Christenson, & Glick, 2020; Druckman & Kam, 2011).”
See Something, Say Something: Correction of Global Health Misinformation on Social Media (2018, background): “However, student samples are often good proxies for the general population, especially for experimental research (Druckman & Kam, 2011).”
(Mis)estimating Affective Polarization (2021, background): “Also, our interest ultimately lies in comparisons across experimental conditions and thus the use of a nonprobability sample is not problematic (Druckman and Kam 2011).”
Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk (2012, unknown): “The former concern is most likely to be a threat if treatment effects are heterogeneous and the composition of the MTurk sample is un-representative of the target population (see Druckman and Kam 2011).”
The Big Five Personality Traits and Attitudes towards Immigrants (2014, background): “…convenience samples (Sibley and Duckitt 2008, 266).2 If the effect sizes vary across population subgroups, and belonging to these groups predicts the probability of inclusion in convenience samples, the estimates obtained using non-representative samples can also be biased (Druckman and Kam 2011).”