1{2 "record_id": "74099967a079fff42f0df3135c0f69cc4e059615",3 "eligible": true,4 "exclusion_reason": null,5 "study": {6 "title": "A Quantitative Examination of Housing Price Determinants in Yogyakarta",7 "year": 2025,8 "doi": "10.23917/determinasi.v3i4.502",9 "country": "Indonesia",10 "region_city": "Yogyakarta",11 "sample_start": null,12 "sample_end": null,13 "property_type": "single_family",14 "price_type": "listing",15 "data_source": "Kaggle secondary dataset 'Yogyakarta Housing Prices (Indonesia)' (2,020 listings; 1,713 complete cases)",16 "document_type": "journal",17 "estimators": [18 "OLS"19 ],20 "spatial_method": "none",21 "time_fe": false,22 "location_fe": false,23 "se_type": "OLS",24 "n_obs_total": 1713,25 "ai_methods": [],26 "notes": "Student paper using a Kaggle listing dataset (year of listings not stated; property type not stated, presumably houses given land area). Linear model in levels (IDR). Table 4 prints unstandardized coefficient, SE, standardized beta, t and p; unstandardized values extracted. Data quality concerns: house area (X4) has mean 1.19e6 m2 and max 2.4e9 m2, bedrooms/bathrooms max 49, VIF > 10 for X1/X2; results should be treated with caution. No stars; p-values printed."27 },28 "models": [29 {30 "model_id": "T4-M1",31 "table": "4",32 "column": "M1",33 "page": 7,34 "dep_var": "housing price (IDR)",35 "dep_transform": "level",36 "estimator": "OLS",37 "n_obs": 1713,38 "r2": 0.428,39 "se_or_t_in_parentheses": "none",40 "sample_subset": "Complete cases from Kaggle dataset; adj R2 0.427"41 }42 ],43 "coefficients": [44 {45 "model_id": "T4-M1",46 "var_name_printed": "X1 (number of bedrooms)",47 "taxonomy_id": "bedrooms",48 "x_transform": "level",49 "x_unit": "count",50 "beta": 88540000.0,51 "se": 39390000.0,52 "t": 2.248,53 "p": 0.025,54 "p_stars": "",55 "ci_lo": null,56 "ci_hi": null,57 "page": 7,58 "confidence": "high",59 "notes": "VIF 10.08"60 },61 {62 "model_id": "T4-M1",63 "var_name_printed": "X2 (number of bathrooms)",64 "taxonomy_id": "bathrooms",65 "x_transform": "level",66 "x_unit": "count",67 "beta": 164200000.0,68 "se": 39390000.0,69 "t": 4.169,70 "p": 0.001,71 "p_stars": "",72 "ci_lo": null,73 "ci_hi": null,74 "page": 7,75 "confidence": "high",76 "notes": "p printed as < .001; VIF 10.26"77 },78 {79 "model_id": "T4-M1",80 "var_name_printed": "X3 (land area)",81 "taxonomy_id": "lot_size",82 "x_transform": "level",83 "x_unit": "m2",84 "beta": 3729000.0,85 "se": 243986.024,86 "t": 15.282,87 "p": 0.001,88 "p_stars": "",89 "ci_lo": null,90 "ci_hi": null,91 "page": 7,92 "confidence": "high",93 "notes": "p printed as < .001"94 },95 {96 "model_id": "T4-M1",97 "var_name_printed": "X4 (house area)",98 "taxonomy_id": "living_area",99 "x_transform": "level",100 "x_unit": "m2",101 "beta": 0.301,102 "se": 0.722,103 "t": 0.417,104 "p": 0.677,105 "p_stars": "",106 "ci_lo": null,107 "ci_hi": null,108 "page": 7,109 "confidence": "medium",110 "notes": "Variable badly scaled in source data (mean 1.19e6 m2, max 2.4e9 m2); coefficient printed as 0.301 (SE 0.722)"111 },112 {113 "model_id": "T4-M1",114 "var_name_printed": "X5 (vehicle slots)",115 "taxonomy_id": "parking",116 "x_transform": "level",117 "x_unit": "count",118 "beta": 160600000.0,119 "se": 44080000.0,120 "t": 3.643,121 "p": 0.001,122 "p_stars": "",123 "ci_lo": null,124 "ci_hi": null,125 "page": 7,126 "confidence": "high",127 "notes": "p printed as < .001"128 }129 ]130}