{"text_format":"2","workbook":"xls","n_sheets":1,"sheets":["report2"],"not_rendered":{"charts":0,"images":0,"macros":0,"external_links":1,"defined_names":1,"comments":0,"pivot_tables":0},"unopened":[],"bounds":{"document_bytes":16777216,"sheet_cells":100000,"run_cost":"one","rows_first":2000,"rows_last":500,"rows_between":2000,"halvings":0,"cell_chars":16384,"cell_head_chars":4096},"cells_cut":0,"cells_raw":0,"read":"whole","date_system":"1900","formulas":"cached_only"}

{"sheet":"report2","index":0,"n_rows":21,"n_cols":5,"rows_kept":21,"cut":false,"hidden":false,"merged":[[0,2,0,3],[0,4,0,5],[1,2,1,3],[1,4,1,5],[2,2,2,3],[2,4,2,5],[3,2,3,3],[5,2,5,3],[7,2,7,3],[8,2,8,3],[9,2,9,3],[10,2,10,3],[12,2,12,3],[14,2,14,3],[15,2,15,3],[19,2,19,3]],"flags":["formulas_cached_only"]}
[null,"1.","Record Nr.",null,"UNINA9910787849103321"]
[null,null,"Autore",null,"O'Brien Robert M."]
[null,null,"Titolo",null,"Age-period-cohort models : approaches and analyses with aggregate data / / Robert M. O'Brien, University of Oregon, Eugene, USA"]
[null,null,"Pubbl/distr/stampa",null,"Boca Raton : , : CRC Press, , [2015]"]
[{"$nulls":4},"©2015"]
[null,null,"ISBN",null,"0-429-08856-6"]
[{"$nulls":4},"1-4665-5153-4"]
[null,null,"Edizione",null,"[1st edition]"]
[null,null,"Descrizione fisica",null,"1 online resource (216 p.)"]
[null,null,"Collana",null,"Chapman and Hall/CRC Statistics in the Social and Behavioral Sciences Series"]
[null,null,"Disciplina",null,"001.42/2"]
[{"$nulls":4},"001.422"]
[null,null,"Soggetti",null,"Cohort analysis"]
[{"$nulls":4},"Age groups - Statistical methods"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references."]
[null,null,"Nota di contenuto",null,"1. Introduction to the age, period, and cohort mix -- 2. Multiple classification models and constrained regression -- 3. Geometry of age-period-cohort (APC) models and constrained estimation -- 4. Estimable functions approach -- 5. Partitioning the variance in age-period-cohort (APC) models -- 6. Factor-characteristic approach -- 7. Conclusions : an empirical example."]
[null,null,null,"Sommario/riassunto","Develop a Deep Understanding of the Statistical Issues of APC AnalysisAge-Period-Cohort Models: Approaches and Analyses with Aggregate Data presents an introduction to the problems and strategies for modeling age, period, and cohort (APC) effects for aggregate-level data. These strategies include constrained estimation, the use of age and/or period and/or cohort characteristics, estimable functions, variance decomposition, and a new technique called the s-constraint approach. See How Common Methods Are Related to Each OtherAfter a general and wide-ranging introductory chapter, the book explain"]