Reader-based Turkish sentence difficulty: stimulus features, trial-level comprehension responses, pairwise preference judgments, and analysis code

This dataset accompanies a manuscript, currently submitted for publication, on reader-based measurement of Turkish sentence reading difficulty. The studyexamines whether morphological, syntactic, and lexical complexity predict comprehension difficulty beyond surface sentence length. The dataset contains everything required to reproduce all quantitative results reported in the manuscript. FILES saha_calismasi_veri_seti_800.xlsx - Sentence pool with expert-checked linguistic features (morpheme density, constituent-phrase count, non-finite verbs, foreign/proper-name count, rare-word ratio, word count). The sheet "selected_sentences" is used; the 787 sentences administered in the field study are a subset. 2_soru_yanitlari-10.csv - Trial-level comprehension responses from the web-based field study (1,480 participants; 22,490 responses), including question type, chosen answer, accuracy, and response time. 3_karsilastirma_tercihleri-4.csv - Trial-level pairwise preference judgments (2,960 judgments). reproduce_analysis.py - A single self-contained Python script that reproduces all tables and in-text statistics directly from the raw files. requirements.txt - Python dependencies. reproduction_results.txt - Console output of a complete run of the analysis script, for reference. README.md - Instructions and a description of the analysis pipeline. HOW TO REPRODUCE Create a fresh virtual environment, install the dependencies (pip install -r requirements.txt), place the three raw data files in one directory, and run: python reproduce_analysis.py --data-dir /path/to/data The script prints every result section by section, labelled with the corresponding manuscript table and section. Runtime is under two minutes. PRIVACY Participants are identified only by an arbitrary integer ID. No names, contact details, or other directly identifying information were collected. ETHICS The study was approved by the Scientific Research and Publication Ethics Committee of the Faculty of Science and Engineering, Afyon Kocatepe University (decision no. 2026/4, 25 February 2026). FUNDING Scientific and Technological Research Council of Türkiye (TÜBİTAK), 1001 programme, grant no. 124E056.