{"id":"W4385324378","doi":"10.5539/ijsp.v12n4p40","title":"An Approximate Confidence Interval for the Variance of Random Effects of One-Way Analysis of Variance in the Completely Randomized Design","year":2023,"lang":"en","type":"article","venue":"International Journal of Statistics and Probability","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Variance (accounting); Confidence interval; Mathematics; Statistics; Monte Carlo method; Coverage probability; Variance-based sensitivity analysis; One-way analysis of variance; Interval (graph theory); Analysis of variance; CDF-based nonparametric confidence interval; Robust confidence intervals; Combinatorics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02757814,0.0001064743,0.0009230526,0.0002989835,0.00003740842,0.00007976264,0.001136785,0.00003608602,0.00002891427],"category_scores_gemma":[0.01818537,0.00005678165,0.0002335729,0.000688143,0.0005866824,0.0001720959,0.00006596665,0.0001217951,2.137916e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002525313,"about_ca_system_score_gemma":0.00008992964,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009182277,"about_ca_topic_score_gemma":0.00001401381,"domain_scores_codex":[0.9943742,0.002400388,0.001682678,0.0001955861,0.001236943,0.0001101594],"domain_scores_gemma":[0.9415551,0.05503372,0.001505061,0.0002685497,0.001602118,0.00003547067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.1895096,0.001806392,0.005405499,0.0004049722,0.00557904,0.00003856592,0.01948364,0.1166686,0.06975296,0.5276392,0.0002959689,0.06341556],"study_design_scores_gemma":[0.01862524,0.0004676096,0.02947,0.00009507522,0.0004004434,0.000006163989,0.0003094458,0.4809759,0.005005868,0.4645598,0.000009554847,0.00007485006],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05234926,0.000177629,0.9460127,0.00022689,0.0002453624,0.0007311045,0.0002366968,0.000001629277,0.00001867502],"genre_scores_gemma":[0.7599975,0.00007850515,0.2398455,0.00002924491,0.00001608731,0.00002275461,0.00000286419,0.000003309768,0.000004198467],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7076483,"threshold_uncertainty_score":0.9900849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1477719726789253,"score_gpt":0.442113446215026,"score_spread":0.2943414735361007,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}