{"id":"W4386911034","doi":"10.1002/jrsm.1669","title":"Evaluation of statistical methods used to meta‐analyse results from interrupted time series studies: A simulation study","year":2023,"lang":"en","type":"review","venue":"Research Synthesis Methods","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Hospital; University of Ottawa","funders":"National Health and Medical Research Council; Monash University; Medical Research Council; Australian Government","keywords":"Statistics; Autocorrelation; Meta-analysis; Random effects model; Context (archaeology); Econometrics; Interrupted Time Series Analysis; Restricted maximum likelihood; Ordinary least squares; Series (stratigraphy); Time series; Mathematics; Variance (accounting); Computer science; Maximum likelihood; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","metaepi_broad","scholarly_communication","insufficient_payload"],"consensus_categories":["metaresearch","metaepi_narrow","insufficient_payload"],"category_scores_codex":[0.917397,0.001282927,0.03611669,0.005990727,0.0003914232,0.001217258,0.005315467,0.0004986093,0.0109426],"category_scores_gemma":[0.9399383,0.0006212661,0.006926229,0.01522246,0.0003508941,0.0003852367,0.001891261,0.001033361,0.005236903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007464926,"about_ca_system_score_gemma":0.001414878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002048661,"about_ca_topic_score_gemma":0.0001394446,"domain_scores_codex":[0.08831113,0.8363052,0.03244431,0.00485144,0.03704466,0.001043232],"domain_scores_gemma":[0.07951949,0.8666249,0.01312878,0.01437908,0.02558024,0.000767538],"domain_codex":"methods","domain_gemma":"methods","domain_candidate":"methods","domain_consensus":"methods","study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006444406,0.0002202973,9.237652e-7,0.00143396,0.05585716,0.000007963249,0.002271139,0.0009932928,0.000008191795,0.00002109772,0.0032543,0.9358672],"study_design_scores_gemma":[0.0004757367,0.0005277792,0.00005363617,0.006552453,0.2724022,0.000002498485,0.01174745,0.08511228,0.00005983052,0.01483626,0.6070718,0.001158106],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"methods","genre_scores_codex":[0.00002269264,0.7872866,0.2009151,0.0001314886,0.0002761565,0.009675543,0.001218858,0.00003121355,0.00044237],"genre_scores_gemma":[0.00004826524,0.2974312,0.6949514,0.000007542089,0.0002088796,0.004188449,0.00008464436,0.0001585169,0.00292107],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.9347091,"threshold_uncertainty_score":0.9999923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9895385164088845,"score_gpt":0.8199393673767278,"score_spread":0.1695991490321567,"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."}}