Selection bias

Related lectures (31)

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Covers the reliability of observational and experimental studies, participant selection, data bias, and result accuracy.

Covers the transition from a comparator to an amplifier, focusing on the different stages and components involved.

Covers the inconsistency in estimates due to endogeneity and introduces the BLP and Control-Function estimation methods.

Explores challenges in natural language generation, decoding algorithms, training issues, and reward functions.

Explores randomness in social processes, focusing on the selection of authority roles.

Explores motivations for check-ins, human mobility patterns, and biases in mobility data from location-based social networks.

Explores the significance of anonymity in avoiding judgment based on personal characteristics and the need to balance it with accountability.

Covers the concept of geometric ergodicity in the context of convergence diagnostics for Markov chains.

Covers an example of Bayesian parameter estimation and the trade-off between bias and variance in supervised learning.

Explores data quality, biases in data, and the importance of good governance practices in urban data settings.