{"id":"W2240102487","doi":"10.1007/s12144-015-9404-0","title":"Using the Gamma Generalized Linear Model for Modeling Continuous, Skewed and Heteroscedastic Outcomes in Psychology","year":2016,"lang":"en","type":"article","venue":"Current Psychology","topic":"Psychometric Methodologies and Testing","field":"Decision Sciences","cited_by":178,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Homoscedasticity; Heteroscedasticity; Psychology; Normality; Econometrics; Outcome (game theory); Linear regression; Linear model; Generalized linear model; Variance (accounting); Statistics; General linear model; Range (aeronautics); Mathematics; Social psychology; Mathematical economics; Engineering; Economics","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.02768444,0.00193656,0.001789903,0.002199857,0.001019133,0.00373531,0.003868656,0.002641971,0.005337352],"category_scores_gemma":[0.09174776,0.001000659,0.003237424,0.003827237,0.001998166,0.003465519,0.003126196,0.005105277,0.001500611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002776245,"about_ca_system_score_gemma":0.005521496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02125395,"about_ca_topic_score_gemma":0.01383419,"domain_scores_codex":[0.9811952,0.01442014,0.0005036615,0.001881018,0.001237594,0.0007624095],"domain_scores_gemma":[0.9515391,0.03934474,0.002017345,0.004199762,0.002447827,0.0004511059],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001034711,0.0007386135,0.07842694,0.0007541919,0.002315162,0.0008796811,0.004136434,0.4269298,0.001696929,0.255434,0.01207905,0.2155745],"study_design_scores_gemma":[0.0001917703,0.000548316,0.01710925,0.0003264476,0.000407558,0.0003460406,0.0009821121,0.6923064,0.001032145,0.2793869,0.007175511,0.0001874379],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06029372,0.0003966272,0.9347233,0.000655294,0.0001721889,0.0004842262,0.0008505623,0.000946915,0.001477151],"genre_scores_gemma":[0.6449842,0.001122005,0.3393406,0.000642646,0.0001607687,0.003294266,0.002602172,0.0005775698,0.007275622],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02768444,"threshold_uncertainty_score":0.1464111,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7652380167565765,"score_gpt":0.5944211459043176,"score_spread":0.1708168708522589,"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."}}