{"id":"W2030152850","doi":"10.1081/sta-120014915","title":"LOG-LINEAR MODELLING OF CHANGE USING LONGITUDINAL SURVEY DATA","year":2002,"lang":"en","type":"article","venue":"Communication in Statistics- Theory and Methods","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Multinomial distribution; Statistics; Variance (accounting); Sampling (signal processing); Mathematics; Longitudinal data; Sampling design; Econometrics; Log-linear model; Independence (probability theory); Linear model; Computer science; Demography; Data mining; Economics; Population","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01139414,0.0001513011,0.0004193909,0.0001049621,0.0001154957,0.00002188996,0.0005992133,0.00008953489,0.0001662931],"category_scores_gemma":[0.007959557,0.000143878,0.00001606138,0.0002351674,0.0003599378,0.0001539227,0.0004380157,0.0002674094,0.000001388423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001933614,"about_ca_system_score_gemma":0.00001459972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000254829,"about_ca_topic_score_gemma":0.0000432585,"domain_scores_codex":[0.9921955,0.006595473,0.0006047146,0.0002773648,0.0001292811,0.000197596],"domain_scores_gemma":[0.9773452,0.0207928,0.0002681586,0.001375242,0.0001518418,0.00006676865],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005126099,0.0001180311,0.002799748,0.000158163,0.00002169579,0.000001550903,0.001042071,0.00001874432,0.00004486838,0.8689181,0.00003747347,0.1267883],"study_design_scores_gemma":[0.0001717806,0.00001999363,0.001590524,0.0001147507,0.00003893523,0.000004280546,0.00007388631,0.345033,0.00004734444,0.6527641,0.00002632043,0.0001150245],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001820585,0.001417454,0.9955468,0.00001394355,0.00005697779,0.0001963151,0.0006647315,0.00001559567,0.0002676599],"genre_scores_gemma":[0.08144924,0.0007227173,0.9176835,0.00002221476,0.00001776984,0.00001072102,0.00005132567,0.00001923056,0.00002332516],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3450143,"threshold_uncertainty_score":0.9528908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7854312983125642,"score_gpt":0.5559545184830741,"score_spread":0.2294767798294901,"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."}}