{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.3456015,0.003566462,0.01063342,0.006263088,0.0008574197,0.005667951,0.004609631,0.004353934,0.006394959],"category_scores_gemma":[0.5880748,0.002298583,0.03545728,0.007470491,0.00150999,0.003556681,0.002921884,0.004760874,0.0008543993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004676053,"about_ca_system_score_gemma":0.006004611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003529989,"about_ca_topic_score_gemma":0.002729552,"domain_scores_codex":[0.6046904,0.3621508,0.01986411,0.004947263,0.007566353,0.0007811249],"domain_scores_gemma":[0.3542681,0.5937907,0.01970687,0.01884647,0.01268489,0.0007029351],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"meta_analysis","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.01299282,0.0004353436,0.01439771,0.1375499,0.4332477,0.0009855003,0.001305354,0.1908546,0.0008693177,0.0364902,0.01107535,0.1597961],"study_design_scores_gemma":[0.01561706,0.005792032,0.007353763,0.06357932,0.372058,0.001126836,0.0006055617,0.3608217,0.003263099,0.1194164,0.04966203,0.0007041343],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01499651,0.08434764,0.8595103,0.004715565,0.002332218,0.02478999,0.004435591,0.001890571,0.002981621],"genre_scores_gemma":[0.2831521,0.03036837,0.6094306,0.002405749,0.0005354765,0.06997572,0.002544627,0.0005392624,0.001048076],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6543985,"threshold_uncertainty_score":0.8069898,"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."}}