01/01/2018 Computer Science Mathematics
DOI: 10.1007/978-3-319-69830-4_4 SemanticScholar ID: 53008057 MAG: 2235769802

Autocorrelated Errors in Experimental Data in the Language Sciences: Some Solutions Offered by Generalized Additive Mixed Models

Publication Summary

A problem that tends to be ignored in the statistical analysis of experimental data in the language sciences is that responses often constitute time series, which raises the problem of autocorrelated errors. If the errors indeed show autocorrelational structure, evaluation of the significance of predictors in the model becomes problematic due to potential anti-conservatism of p-values.

CAER Authors

Avatar Image for Cécile De Cat

Prof. Cécile De Cat

University of Leeds - Professor of Linguistics

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