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Binary logistic GEE results for the Path ROI (per time window of interest).

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Figshare2015-12-02 更新2026-04-29 收录
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https://figshare.com/articles/dataset/_Binary_logistic_GEE_results_for_the_Path_ROI_per_time_window_of_interest_/728628
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Table shows GEE modelling results for occurrences of looks to the Path ROI as a function of Verb Speed (fast vs. slow) and Time (continuous predictor referring to the 50 ms time-bins per window). Shown are the by-participant/by-item GEE parameter estimates and corresponding SEs (both in logit units) along with generalised score chi square statistics and related p-values (at df = 1). As for interactions (S×T), a positive parameter estimate indicates a more positive slope for the Time predictor in the fast than in the slow Verb Speed condition. ΔQIC refers to the goodness of fit of the Verb Speed×Time model in relation to a competitor Agent-Verb Suitability×Lexical Frequency×Time model (negative ΔQICs indicate superior fit of the Verb Speed×Time model).
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2015-12-02
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