JGSSデータによる父学歴の欠損メカニズムの分析―〈わからない〉と〈無回答〉の違い―
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2 An Analysis on the Missing Mechanism of Fathers Education in JGSS: The difference between DK and NA Tokio YASUDA For some studies of intergenerational social mobility, you sometimes need to know education experienced by fathers of survey respondents. But, fathers education is one of the questions that often occur much missing data. Missing data may cause some biases for statistical analyses. You need to specify the missing mechanism of fathers education in order to resolve the problem. Some studies examined the mechanism, but the analyses by those studies only made unclear conclusion. In this paper, the missing mechanism of fathers education was made clear by the analysis of JGSS data. The reason for which the analysis was possible was that JGSS had made different codes indicating each of Do not know and No answer. The result of the analysis indicated that respondents cohort and education had significant effects on the missing of fathers education. The result implied that the missing of fathers education would be ignorable when you control those variables. Key words: JGSS, missing data, intergenerational social mobility 243
3 missing data 1 unit nonresponse item nonresponse listwise deletion Groves et al unit nonresponse item nonresponse 244
4 SSM a; 2000b 1985 SSM,2000b (1) b 1995 SSM 2000a (2)
5 JGSS 2000a; 2000bJGSS SSM 2 1 JGSS , a; 2000b JGSS 246
6 JGSS a; 2000b SSM JGSS SSM 1 JGSS JGSS JGSS 2000a; 2000b 2.2 JGSS JGSS General Social Surveys ,893 2,7902,9533,663 12,299 10,537 JGSS 247
7 , SSM 2000a ABCD 1 1, 2000b Fay1986Baker & Laird b
8 A: D: D: B: C: (8.6) 4 (2.5) 40 (12.5) 9 (2.8) 85 (18.6) 24 (5.2) 139 (14.8) 37 (3.9) 8 (10.7) 0 (0.0) 58 (13.7) 12 (2.8) 126 (22.3) 28 (4.9) 192 (18.0) 40 (3.8) (7.9) 10 (3.7) 76 (15.8) 17 (3.5) 91 (23.2) 24 (6.1) 188 (16.5) 51 (4.5) 13 (7.6) 3 (1.8) 127 (19.6) 33 (5.1) 119 (24.2) 24 (4.9) 259 (19.8) 60 (4.6) (10.5) 6 (1.6) 106 (18.3) 17 (2.9) 53 (29.1) 6 (3.3) 199 (17.4) 29 (2.5) 38 (10.5) 10 (2.8) 145 (19.0) 18 (2.4) 59 (26.6) 4 (1.8) 242 (17.9) 32 (2.4) (6.7) 11 (2.9) 68 (17.7) 8 (2.1) 11 (25.0) 0 (0.0) 104 (12.9) 19 (2.4) 45 (10.1) 13 (2.9) 116 (19.9) 19 (3.3) 9 (24.3) 1 (2.7) 170 (15.9) 33 (3.1) (6.6) 8 (2.2) 59 (16.1) 10 (2.7) 9 (23.1) 1 (2.6) 92 (11.9) 19 (2.5) 28 (6.1) 4 (0.9) 68 (14.6) 19 (4.1) 6 (27.3) 0 (0.0) 102 (10.8) 23 (2.4)
9 R R R = = 1 = 1 = f abcdr a =, b =, c = 2 =, d = 2 = ; 5 = 5 = = 3 = 1 = r = 2 = 3 = f abcd2 f abcd3 C A, B, C, D A, B, C, D R B C [BR][CR] EM Dempster et al., 1977; MacLachlan & Krishnan, 1997 fˆ abcdr EM L 2 2 L ( f ˆ ) ( ˆ abcd1 f abcd1 + 2 f ab d 2 log f ab d 2 f ab d 2 ) + 2 f ab d 3 log( f ab d 3 f ab 3 ) = 2 2 f ˆ abcd1 log d 250
10 2 p L 2 p [DR] [BR] [AR][CR] [AR][BR] [BR][DR] [AR][BR][CR] [AR][BR][DR] [AR][CR][DR] [BR][CR][DR] [AR][BR][CR][DR] [BR][DR] [BR][DR] [BR][CR][DR] BD (3) 3 [BR][DR] 251
11 br (1930, ) exp(-0.14)0.87 exp() r R = br (B, R) = (1930, ) (B, R) = (1940, ) (B, R) = (1950, ) (B, R) = (1960, ) (B, R) = (1970, ) dr (D, R) = (, ) (D, R) = (, ) (D, R) = (, ) r R = br (B, R) = (1930, ) (B, R) = (1940, ) (B, R) = (1950, ) (B, R) = (1960, ) (B, R) = (1970, ) dr (D, R) = (, ) (D, R) = (, ) (D, R) = (, )
12 df48l p0.795 [BR][DR] (4) b SSM, 2000a 253
13 SSM SSM SSM 2000b SSM, 2000b SSM JGSS
14 JGSS 1950 ignorable nonignorable General Social SurveysJGSS SSJ (1) 255
15 (2) b a a2000b (3) [BDR] df30l p0.786 [BR][DR] (4) df50l p0.403 Baker, Stuart G. and Laird, Nan M. 1988, Regression Analysis for Categorical Variables With Outcome Subject to Nonignorable Nonresponse, Journal of the American Statistical Association, 83(401), Dempster, A. P., Laird, N. M., and Rubin, D. B., 1977, Maximum Likelihood From Incomplete Data Via the EM Algorithm (With Discussion), Journal of the Royal Statistical Society, Ser.B, 39(1), Fay, Robert E Causal Models for Patterns of Nonresponse, Journal of the American Statistical Association, 81(394), Groves, Robert M., Dillman, Don A., Eltinge, John L., and Little, Roderick J. A. (eds.), 2001, Survey Nonresponse, John Wiley & Sons, Inc. McLachlan, Geoffrey J. and Krishnan, Thriyambakam, 1997, The EM Algorithm and Extensions, John Wiley & Sons, Inc., 2000a, : 1995 SSM,, 5, , 2000b, :,, 15(1),
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Title < 論文 > 公立学校における在日韓国 朝鮮人教育の位置に関する社会学的考察 : 大阪と京都における 民族学級 の事例から Author(s) 金, 兌恩 Citation 京都社会学年報 : KJS = Kyoto journal of so 14: 21-41 Issue Date 2006-12-25 URL http://hdl.handle.net/2433/192679 Right
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101 On the Complement Structure of Bare Infinitive Verbs Kazuko INOUE The purpose of this paper is to argue that the infinitival and participial complements of perception verbs and causative verb have,
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SUMMARY This paper surveys the foot-and-mouth disease (FMD) control policy implemented by the national and Miyazaki prefectural governments during the pandemic from April to July 2010. Several lessons
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