EEG-Based Sleep Stage Classification — Meta-Analysis Summary & Reference Implementation

This dataset accompanies the doctoral thesis "A Comparative Meta-Analysis of Feature Extraction Methods Used in EEG-Based Sleep Stage Classification" (Demirci, Selçuk University Institute of Natural and Applied Sciences, 2026). It contains the per-stage F1 extraction CSVs (single-reviewer strict and four-source consensus), the publication-ready summary workbook with 16 sheets, the reference Python implementation that reproduces the pooled F1 values reported in Table 4.7, the pseudocode for Appendix EK-11, and a README describing the file structure and reproducibility steps. The pooled estimates use a DerSimonian-Laird random-effects model on the logit scale with a 1/sqrt(N) standard error proxy (Peters et al., 2006) and IntHout 95% prediction intervals. All five sleep stages (W, N1, N2, N3, REM) are reproduced within 0.05 absolute tolerance of the thesis values.