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- 岡本 政人
- 独立行政法人統計センター研究センター
書誌事項
- タイトル別名
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- Extension of Bayesian Cohort Models with Interaction Effects
- コウゴ サヨウ コウカ オ コウリョ シタ ベイズガタ コウホート モデル ノ カクチョウ
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抄録
The Bayesian cohort model was introduced by Takashi Nakamura in 1982. His model succeeded in overcoming the identification problem in cohort analysis by setting up an assumption that successive parameters change gradually. Subsequently, he incorporated age-by-period interaction effects into his original model. This paper presents the Bayesian cohort models with different types of interaction effects, said to be difficult to realize, such as age-by-cohort, cohort-by-age, period-by-cohort and cohort-by-period as well as period-by-age. These new models are applied to analysis of liquor consumption in Japan. In addition, this paper shows interactions with other factors are also among candidates for components of appropriate models, taking up a life-stage cohort model as an example. The life-stage cohort analysis proposed in this paper is to make a study of household cohorts classified according to the birth year of the eldest child, regarded as aging as the eldest child grows older. The study reveals that interaction effects between age of the eldest child and number of children living together are essential to analyze a share of seafood in food consumption.
収録刊行物
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- 応用統計学
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応用統計学 32 (3), 145-162, 2003
応用統計学会
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キーワード
詳細情報 詳細情報について
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- CRID
- 1390001204441908352
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- NII論文ID
- 10012746957
- 10013687046
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- NII書誌ID
- AN00330942
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- ISSN
- 18838081
- 02850370
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- NDL書誌ID
- 6892540
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- NDL
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- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可