(X) (Y ) Y = intercept + c X + e (1) e c c M = intercept + ax + e (2) a Y = intercept + cx + bm + e (3) (1) X c c c (3) b X M Y (indirect effect) a b
|
|
|
- あいと ふじつぐ
- 5 years ago
- Views:
Transcription
1 (mediation analysis) Figure 1 X Y M (mediator) mediation model Baron and Kenny (1986) 1 1) mediated moderation ( moderated mediation) 2) (multilevel mediation model) a M b X c (c ) Y 1: Baron and Kenny (1986) a b c c a b supressor variable model 2, murakou@orion.ocn.ne.jp. 1 Baron and Kenny (1986) Maassen & Bakker (2001) 1
2 (X) (Y ) Y = intercept + c X + e (1) e c c M = intercept + ax + e (2) a Y = intercept + cx + bm + e (3) (1) X c c c (3) b X M Y (indirect effect) a b 1 c c X Y M X Y c M c c c c = a b (4) c M c 1 X Y X Y M (complete mediation model) c (partial mediation model) Kenny Judd & Kenny (1981) Baron & Kenny (1986) 1.2 X Y, mediation effect MacKinnon, Lockwood, Hoffman, West, and Sheets (2002) MacKinnon (2008) 2
3 a b σ ab z = a b σ ab (5) % MacKinnon et al. (2002) Sobel s test Aroian (1944) a b (4) c c a b c c (Clogg et al., 1992 ) Sobel s test Sobel (1982) a b σ ab = a 2 σ 2 b + b2 σ 2 a (6) σ a, σ b a b (delta method) X f(x) V ar(f(x)) = ( f(x) X )2 (V ar(x)) (7) X f(x) V ar(f(x)) = d V d (8) V X f(x) X d Mplus model constraint f(a, b) = a b a b b a d = (b, a) X ( ) σa 2 0 V = 0 σb 2 (6) (8) 1 0 a b 0 1 (MacKinnon et al., 1995) Aroian (1944) s test 1 2 Aroian (1944) a b σ ab = (9) a 2 σ 2 b + b2 σ 2 a + σ 2 aσ 2 b (10) 3
4 Sobel s test Sobel s test Distribution of a product method PRODCLIN 1.96 critical value (confidence interval) 3 95% 0 a b Distribution of a product method Springer & Thompson (1966) Table MacKinnon, Fritz, Williams, & Lockwood (2007) PROD- CLIN (distribution of the PRODuct Confidence Limits for INdirect effects) davidpm/ripl/prodclin/ a, b, σ a, σ b a b 0 0 X M t 2 t critical value Table MacKinnon Website 4 MacKinnon et al. (2004) Empirical-M method 2 critical value Table MacKinnon Website Bootstrapping method 1 a b davidpm/ripl/mediate.htm 5 davidpm/ripl/freqdist.pdf 4
5 95% 6 0 nonparametric bootstrapping SAS R N N a b a b a b 7 parametric bootstrapping (Efron & Tibshirani, 1993) a b a b 95% bootstrap a b Efron & Tibshirani, 1993 bias-corrected bootstrapping method MacKinnon et al. (2004) bootstrapping method bias-corrected bootstrap distribution of a product method parametric bootstrapping AMOS, EQS, Mplus SEM 8 distribution of a product method bias-corrected bootstrapping PRODCLIN bootstrapping 2 (X M 1 M 2 Y bootstrapping (SEM) (structural equation modeling; SEM) Baron and Kenny (1986) Figure 1 c bootstrapping SEM Baron and Kenny (1986) SEM 9 Figure 1 X Y SEM 1 (full information maximum likelihood method) N N 1 8 SEM Figure 1 bootstrapping 9 SEM t z 5
6 Baron and Kenny (1986) SEM SEM (multiple mediator model) a b a b c MacKinnon et al. (2002) Baron and Kenny (1986) a b c Baron and Kenny (1986) a, b, c H 0 : a b = 0 vs. H 1 : a b 0 (11) H 0 : a = 0 OR b = 0 (12) a b a = 0 b = 0 2 Moderated mediation model 2.1 mediation moderation mediation X Y M moderation X Y Z (moderator, moderator variable) X Z (Baron and Kenny, 1986) Y = intercept + c XX + c ZZ + c XZXZ + e (13) 6
7 X Z 10 X Z XZ X Z (Cronbach, 1987) Y = intercept + (c X + c XZ Z)X + c ZZ + e (14) X Z 2.2 moderated mediation model 2 moderated mediation Figure 1 a, b, c Z Z a b Z a b moderated mediation Z Figure 1 SEM Z mediated moderation Muller, Judd, and Yzerbyt (2005) Edwards and Lambert (2007) moderated mediation model Figure 2 moderation effect Z mediated moderation c XZ Edwards and Lambert (2007) Figure 2 moderated path analysis a X + a XZ Z M b M + b MZ Z X c X + c XZ Z (c X + c XZ Z) Y 2: moderated mediation model M M = intercept + a X X + a Z Z + a XZ XZ + e (15) 10 Z X 7
8 (2) a XZ X M Z Y Y = intercept + c X X + c XZ XZ + b M M + b MZ MZ + d Z Z + e (16) (3) Z moderator +1SD -1SD moderator bootstrap Edwards and Lambert (2007) SPSS 2.3 mediated moderation? mediated moderation mediated moderation mediated moderation Z mediated moderation Muller et al. (2005) Edwards and Lambert (2007) mediated moderation moderated path analysis (Figure 2) moderation mediated moderation Figure?? a XZ Figure?? (moderated path model) moderated mediation mediated moderation 3 (multilevel mediation model, multilevel mediation analysis) (Hierarchical linear model; HLM) (multilevel structural equation modeling; ML-SEM) Krull and MacKinnon (1999, 2001) (e.g., Bauer, Preacher, & Gil, 2006; Kenny, Bolger, & Korchmaros, 2003) Preacher 11 HLM (Zhang, Zyphur, & Preacher, 2009) ML-SEM (Preacher, Zhphur, & Zhang, in press) 11 8
9 = Krull and MacKinnon (1999, 2001) (Kreft & De Leeuw, 1998) 2 1 Preacher X M Y 1 M Y Figure X M Y 1 2 9
10 3.3 HLM HLM ML-SEM HLM X j Y ij X 2 1 i Level 1 : Y ij = β (1) 0j + r(1) ij (17) Level 2 : β (1) 0j = γ (1) 00 + γ(1) 01 X j + u (1) 0j (18) Level 1 : M ij = β (2) 0j + r(2) ij (19) Level 2 : β (2) 0j = γ (2) 00 + γ(2) 01 X j + u (2) 0j (20) Level 1 : Y ij = β (3) 0j + β(3) 1j M ij + r (3) ij (21) Level 2 : β (3) 0j = γ (3) 00 + γ(3) 01 X j + u (3) 0j (22) β (3) 1j = γ (3) 10 (21) M ij γ (3) M ij 2 aggregate M.j 1 2 grand-mean centering 2 group-mean centering 12 (21) 12 Enders and Tofighi (2007) Y ij X ij grand-mean centering 2 X.j grand-mean centering Level 1 : Y ij = β (a) 0j + β(a) 1j X ij + r (a) ij (23) Level 2 : β (a) 0j β (a) 1j = γ (a) 00 + γ(a) 01 X.j + u (a) 0j (24) = γ (a) 10 (25) X.j γ (a) 01 1 X ij X.j 2 X.j 1 X ij (over and above) contextual effect compositional effect 10
11 (22) Level 1 : Y ij = β (4) 0j + β(4) 1j (M ij M.j ) + r (4) ij (30) Level 2 : β (4) 0j = γ (4) 00 + γ(4) 01 X j + γ (4) 02 M.j + u (4) 0j (31) β (4) 1j = γ (4) 10 1 group-mean centering 2 M.j 1 2 aggregation Figure 3 Preacher et al. (in press) レベル 2 (2) γ 01 M.j (4) γ 02 Xj (4) γ 01 (1) 01 ( γ ) Y M 個々の得点 X Y Mij (4) γ 10 レベル 1 Y 3: Multilevel mediation model group-mean centering group-mean centering Level 1 : Y ij = β (b) 0j + β(b) 1j (X ij X.j ) + r (b) ij (26) Level 2 : β (b) 0j β (b) 1j = γ(b) 00 + γ(b) 01 X.j + u (b) 0j (27) = γ(b) 10 (28) group-mean centering (Enders & Tofighi, 2007) γ (b) 01 γ(b) 10 contextual effect 2 contextual effect γ (a) 01 = γ(b) 01 γ(b) 10 (29) (Ludtke et al., 2009) 1 2 group-mean centering 11
12 Zhang et al. (2009) 3.4 ML-SEM ML-SEM 1 2 HLM 1 X ij X.j ML-SEM X ij = µ + u j + r ij (32) 1 u j 2 r ij 2 ML-SEM ML-SEM straightforward 2 ML-SEM Mplus Preacher HP 14 2 between 2 1 between/within (4) 2 2 Sobel test 15 Preacher et al. (in press) nonparametric bootstrapping parametric bootstrapping Mplus 2 moderated mediation model multilevel mediation model Bauer et al. (2006) HLM 13 2 HLM ML-SEM (Ludtke et al., 2009) socio-economic status (SES) aggregation Ludtke et al. (2009) Marsh et al. (in press) 14 preacher/syntax appendix pdf 15 Mplus model constraint Sobel s test 12
13 4 References Aroian, L. A. (1944). The probability function of the product of two normally distributed variables. Annals of Mathematical Statistics, 18, Baron, R. M. & Kenny, D. A. (1986). The moderator?mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, Bauer, D. J., Preacher, K. J., & Gil, K. M. (2006). Conceptualizing and testing random indirect effects and moderated mediation in multilevel models: New procedures and recommendations. Psychological Methods, 11, Edwards, J. R., & Lambert, L. S. (2007). Methods for integrating moderation and mediation: A general analytical framework using moderated path analysis. Psychological Methods, 12, Efron, B. & Tibshirani, R. (1993). An introduction to the bootstrap. Boca Raton, FL: Chapman & Hall/CRC. Judd, C. M., & Kenny, D. A. (1981). Process analysi: Estimating mediation in treatment evaluations. Evaluation Review, 5, Kenny, D. A., Korchmaros, J. D., & Bolger, N. (2003). Lower level mediation in multilevel models. Psychological Methods, 8, Kreft, I., & De Leeuw, J. (1998). Introducing multilevel modeling. London: Sage ( (2006). ) Krull, J. L., & MacKinnon, D. P. (1999). Multilevel mediation modeling in group-based intervention studies. Evaluation Review, 23, Krull, J. L., & MacKinnon, D. P. (2001). Multilevel modeling of individual and group level mediated effects. Multivariate Behavioral Research, 36, Ludtke, O., Marsh, H. W., Robitzsch, A., Trautwein, U., Asparouhov, T., & Muthen, B. (2008). The multilevel latent covariate model: A new, more reliable approach to group-level effects in contextual studies. Psychological Methods, 13, MacKinnon, D. P. (2008). Introduction to statistical mediation analysis. Mahwah, NJ: Erlbaum. MacKinnon, D. P., Fairchild, A. J., & Fritz, M. S. (2007). Mediation analysis. Annual Review of Psychology, 58, MacKinnon, D. P., Fritz, M. S., Williams, J., & Lockwood, C. M. (2007). Distribution of the product confidence limits for the indirect effect: Program PRODCLIN. Behavior Research Methods, 39, MacKinnon, D. P., Lockwood, C. M., Hoffman, J. M., West, S. G., & Sheets, V. (2002). A comparison of methods to test the significance of the mediated effect. Psychological Methods, 7, MacKinnon, D. P., Lockwood, C. M., & Williams, J. (2004). Confidence limits for the indirect effect: Distribution of the product and resampling methods. Multivariate Behavioral Research, 39, MacKinnon, D. P., Warsi, G., & Dwyer, J. H. (1995). A simulation study of mediated effect measures. Multivariate Behavioral Research, 30,
14 Maassen, G. H., & Bakker, A. B. (2001). Suppressor variables in path models: Definitions and interpretations. Sociological Methods & Research, 30, Marsh, H. W., Ludtke, O., Robitzsch, A., Trautwein, U., Asparouhov, T., Muthen, B., & Nagensgast, B. (in press). Multilevel fully latent-variable models of contextual effects: Integrating multilevel and structural equation approaches with multiple indicators to control. Muller, D., Judd, C. M., & Yzerbyt, V. Y. (2005). When moderation is mediated and mediation is moderated. Journal of Personality and Social Psychology, 89, Preacher, K. J., Zyphur, M. J., & Zhang, Z. (in press). A general multilevel SEM framework for assessing multilevel mediation. Psychological Methods. Sobel, M. E. (1982). Asymptotic confidence intervals for indirect effects in structural equation models. Sociological Methodology, 13, Springer, M. D. & Thompson, W. E. (1966). The distribution of products of independent random variables. SIAM Journal of Applied Mathematics, 14, Zhang, Z., Zyphur, M. J., & Preacher, K. J. (2009). Testing multilevel mediation using hierarchical linear models: Problems and solutions. Organizational Research Methods, 12,
X X X Y R Y R Y R MCAR MAR MNAR Figure 1: MCAR, MAR, MNAR Y R X 1.2 Missing At Random (MAR) MAR MCAR MCAR Y X X Y MCAR 2 1 R X Y Table 1 3 IQ MCAR Y I
(missing data analysis) - - 1/16/2011 (missing data, missing value) (list-wise deletion) (pair-wise deletion) (full information maximum likelihood method, FIML) (multiple imputation method) 1 missing completely
越智59.qxd
Social Skills Training; SST SST Social Skills, SST, ;, SST, SST SST, ;, ; DeRosier & Marcus,, ;, a b SST Ladd & Mize, ; Hansen, Nagle, & Meyer,,, A BC SST SST SST SST SST SST, SST Goldstein & McGinnis,
1 Stata SEM LightStone 4 SEM 4.. Alan C. Acock, Discovering Structural Equation Modeling Using Stata, Revised Edition, Stata Press 3.
1 Stata SEM LightStone 4 SEM 4.. Alan C. Acock, 2013. Discovering Structural Equation Modeling Using Stata, Revised Edition, Stata Press 3. 2 4, 2. 1 2 2 Depress Conservative. 3., 3,. SES66 Alien67 Alien71,
66-1 田中健吾・松浦紗織.pwd
Abstract The aim of this study was to investigate the characteristics of a psychological stress reaction scale for home caregivers, using Item Response Theory IRT. Participants consisted of 337 home caregivers
: (EQS) /EQUATIONS V1 = 30*V F1 + E1; V2 = 25*V *F1 + E2; V3 = 16*V *F1 + E3; V4 = 10*V F2 + E4; V5 = 19*V99
218 6 219 6.11: (EQS) /EQUATIONS V1 = 30*V999 + 1F1 + E1; V2 = 25*V999 +.54*F1 + E2; V3 = 16*V999 + 1.46*F1 + E3; V4 = 10*V999 + 1F2 + E4; V5 = 19*V999 + 1.29*F2 + E5; V6 = 17*V999 + 2.22*F2 + E6; CALIS.
Kobe University Repository : Kernel タイトル Title 著者 Author(s) 掲載誌 巻号 ページ Citation 刊行日 Issue date 資源タイプ Resource Type 版区分 Resource Version 権利 Rights DOI
Kobe University Repository : Kernel タイトル Title 著者 Author(s) 掲載誌 巻号 ページ Citation 刊行日 Issue date 資源タイプ Resource Type 版区分 Resource Version 権利 Rights DOI 平均に対する平滑化ブートストラップ法におけるバンド幅の選択に関する一考察 (A Study about
1 Stata SEM LightStone 3 2 SEM. 2., 2,. Alan C. Acock, Discovering Structural Equation Modeling Using Stata, Revised Edition, Stata Press.
1 Stata SEM LightStone 3 2 SEM. 2., 2,. Alan C. Acock, 2013. Discovering Structural Equation Modeling Using Stata, Revised Edition, Stata Press. 2 3 2 Conservative Depress. 3.1 2. SEM. 1. x SEM. Depress.
dvi
2017 65 2 185 200 2017 1 2 2016 12 28 2017 5 17 5 24 PITCHf/x PITCHf/x PITCHf/x MLB 2014 PITCHf/x 1. 1 223 8522 3 14 1 2 223 8522 3 14 1 186 65 2 2017 PITCHf/x 1.1 PITCHf/x PITCHf/x SPORTVISION MLB 30
1 Tokyo Daily Rainfall (mm) Days (mm)
( ) r-taka@maritime.kobe-u.ac.jp 1 Tokyo Daily Rainfall (mm) 0 100 200 300 0 10000 20000 30000 40000 50000 Days (mm) 1876 1 1 2013 12 31 Tokyo, 1876 Daily Rainfall (mm) 0 50 100 150 0 100 200 300 Tokyo,
日本統計学会誌, 第44巻, 第2号, 251頁-270頁
44, 2, 205 3 25 270 Multiple Comparison Procedures for Checking Differences among Sequence of Normal Means with Ordered Restriction Tsunehisa Imada Lee and Spurrier (995) Lee and Spurrier (995) (204) (2006)
”Лï‡Æ™²“¸_‚æ4“ƒ__‘dflÅPDF‘‚‡«‘o‡µ.pdf
No.4 1 1 2 No.4 No.4 2 3 4 5 6 No.4 7 8 9 No.4 10 3 No.4 No.4 4 No.4 No.4 1 2 3 4 5 6 7 8 9 10 Assessment Class and Conformity: A Study in Values, With a Reassessment Research in Social Stratification
Meas- urement Angoff, W. H. 19654 Equating non-parallel tests. Journal of Educational Measurement, 1, 11-14. Angoff, W. H. 1971a Scales, norms and equivalent scores. In R. L. Thorndike (Ed.) Educational
20/September/ (2007) (2007) Berger- ( 2000) Cinii 8 Sociological Abstracts relative deprivation ) *1 (2007) *2 2 4 δ Boudon-Kosaka
20/September/2009 1 (2007) (2007) Berger- ( 2000) Cinii 8 Sociological Abstracts relative deprivation 98 2009 9 11 ) *1 (2007) *2 2 4 δ Boudon-Kosaka (Kosaka 1986) Boudon-Kosaka- ) 1 1 3 Boudon-Kosaka
Separating multiple processes in implicit social cognition: The quad model of implicit task performance. Conrey, F. R., Sherman, J. W., Gawronski, B.,
Separating multiple processes in implicit social cognition: The quad model of implicit task performance. Conrey, F. R., Sherman, J. W., Gawronski, B., Hugenberg, K., & Groom, C. J. (2005). Journal of Personality
Hi-Stat Discussion Paper Series No.248 東京圏における 1990 年代以降の住み替え行動 住宅需要実態調査 を用いた Mixed Logit 分析 小林庸平行武憲史 March 2008 Hitotsubashi University Research Unit
Hi-Stat Discussion Paper Series No.248 東京圏における 1990 年代以降の住み替え行動 住宅需要実態調査 を用いた Logit 分析 小林庸平行武憲史 March 2008 Hitotsubashi University Research Unit for Statistical Analysis in Social Sciences A 21st-Century
2 251 Barrera, 1986; Barrera, e.g., Gottlieb, 1985 Wethington & Kessler 1986 r Cohen & Wills,
2014 25 1 1 11 1 3,085 100 1 1988 e.g., 2000 3 e.g., 2005; 1999 100 1960 100 2012 2 6 23 1 98.2 1999 1999 3 65.3 1999 1996 1 21 e.g., 1999 3 1 2 251 Barrera, 1986; 1993 1 2 2001 3 2001 Barrera, 1981 1993
The Japanese Journal of Health Psychology, 29(S): (2017)
Journal of Health Psychology Research 2017, Vol. 29, Special issue, 139 149Journal of Health Psychology Research 2016, J-STAGE Vol. Advance 29, Special publication issue, 139 149 date : 5 December, 2016
規則帰納における方向性
2002 3 JCSS-TR-43 603-8577 56-1 hat@lt.ritsumei.ac.jp 152-8552 2-12-1 Copyright c 2002 by Masasi Hattori, Koji Nakajima, & Masanori Nakagawa. All rights reserved. 464-8601 : 052-789-4891 FAX : 052-789-4752
Vol. 29, No. 2, (2008) FDR Introduction of FDR and Comparisons of Multiple Testing Procedures that Control It Shin-ichi Matsuda Department of
Vol. 29, No. 2, 125 139 (2008) FDR Introduction of FDR and Comparisons of Multiple Testing Procedures that Control It Shin-ichi Matsuda Department of Information Systems and Mathematical Sciences, Faculty
第13回：交差項を含む回帰・弾力性の推定
13 2018 7 27 1 / 31 1. 2. 2 / 31 y i = β 0 + β X x i + β Z z i + β XZ x i z i + u i, E(u i x i, z i ) = 0, E(u i u j x i, z i ) = 0 (i j), V(u i x i, z i ) = σ 2, i = 1, 2,, n x i z i 1 3 / 31 y i = β
x T = (x 1,, x M ) x T x M K C 1,, C K 22 x w y 1: 2 2
Takio Kurita Neurosceince Research Institute, National Institute of Advanced Indastrial Science and Technology takio-kurita@aistgojp (Support Vector Machine, SVM) 1 (Support Vector Machine, SVM) ( ) 2
２
fukui@econ.tohoku.ac.jp http://www.econ.tohoku.ac.jp/~fukui/site.htm 200 7 Cookbook-style . (Inference) (Population) (Sample) f(x = θ = θ ) (up to parameter values) (estimation) 2 3 (multicolinearity)
わが国企業による資金調達方法の選択問題
* takeshi.shimatani@boj.or.jp ** kawai@ml.me.titech.ac.jp *** naohiko.baba@boj.or.jp No.05-J-3 2005 3 103-8660 30 No.05-J-3 2005 3 1990 * E-mailtakeshi.shimatani@boj.or.jp ** E-mailkawai@ml.me.titech.ac.jp
発達心理学研究 第24巻 第3号
2013 24 3 337 347 母子間の漸成発達主題獲得の関連性が青年のアイデンティティ達成に及ぼす影響 104 21 83 1 2 3 4 キーワード 漸成発達, 母子間の関連性, アイデンティティ 問題と目的 Erikson 1959/2011 2000; Lerner & Busch-Rossnagle, 1981; Newman & Newman, 2005 Erikson Erikson
Jpn. J. Personality 19(2): (2010)
2010 19 2 146 156 2010 1) 2) 2 120 60 2 (e.g., Mikulincer & Shaver, 2007) 1) (B) 20730415 69 2008 2) 3) Hazan & Shaver (1987) (Mikulincer & Shaver, 2007) 3 3 3 1 3) 2 2 (e.g., 2001) (Bowlby, 1969/1982)
Stepwise Chow Test * Chow Test Chow Test Stepwise Chow Test Stepwise Chow Test Stepwise Chow Test Riddell Riddell first step second step sub-step Step
Stepwise Chow Test * Chow Test Chow Test Stepwise Chow Test Stepwise Chow Test Stepwise Chow Test Riddell Riddell first step second step sub-step Stepwise Chow Test a Stepwise Chow Test Takeuchi 1991Nomura
01.Œk’ì/“²fi¡*
AIC AIC y n r n = logy n = logy n logy n ARCHEngle r n = σ n w n logσ n 2 = α + β w n 2 () r n = σ n w n logσ n 2 = α + β logσ n 2 + v n (2) w n r n logr n 2 = logσ n 2 + logw n 2 logσ n 2 = α +β logσ
時間割引：双曲割引と弱加法性
Discussion aper No. 666 June 2006 The Institute of Social and Economic Research Osaka University 6-1 Mihogaoka, Ibaraki, Osaka 567-0047, Japan Time Discounting: Declining Impatience and Interval Effect
80 X 1, X 2,, X n ( λ ) λ P(X = x) = f (x; λ) = λx e λ, x = 0, 1, 2, x! l(λ) = n f (x i ; λ) = i=1 i=1 n λ x i e λ i=1 x i! = λ n i=1 x i e nλ n i=1 x
80 X 1, X 2,, X n ( λ ) λ P(X = x) = f (x; λ) = λx e λ, x = 0, 1, 2, x! l(λ) = n f (x i ; λ) = n λ x i e λ x i! = λ n x i e nλ n x i! n n log l(λ) = log(λ) x i nλ log( x i!) log l(λ) λ = 1 λ n x i n =
02古郡氏李氏_a_4.indd
55 2014 e.g2004 2005 2001 1980 101990 1 2 2002 2003 25,000 20038,000 2013 10 2013 1,787 21.623 4,302 1 HUD portal.hud. gov/.../huddoc?id=pih2013 15.pdf... 2 14 105 30,000 25,000 25,296 20,000 15,000 10,000
dvi
2017 65 2 217 234 2017 Covariate Balancing Propensity Score 1 2 2017 1 15 4 30 8 28 Covariate Balancing Propensity Score CBPS, Imai and Ratkovic, 2014 1 0 1 2 Covariate Balancing Propensity Score CBPS
ohpmain.dvi
fujisawa@ism.ac.jp 1 Contents 1. 2. 3. 4. γ- 2 1. 3 10 5.6, 5.7, 5.4, 5.5, 5.8, 5.5, 5.3, 5.6, 5.4, 5.2. 5.5 5.6 +5.7 +5.4 +5.5 +5.8 +5.5 +5.3 +5.6 +5.4 +5.2 =5.5. 10 outlier 5 5.6, 5.7, 5.4, 5.5, 5.8,
e.g., Mahoney, Vandell, Simpkins, & Zarrett, Bohnert, Fredricks, & Randall2010 breadth intensitydurationengagement e.g., Mahone
2014 25 4 453465 1 670 6 1 2 2008, 2009 2002 e.g., 2002; 1999 100 1 2 2013; 2002; 1999 1 2007 2009 2006; 20082006 2013 454 254 e.g., Mahoney, Vandell, Simpkins, & Zarrett, 2009 1 23 2013 Bohnert, Fredricks,
LET2009
Language Education & Technology, 46 (2010) pp. 1 19 Multiple testing of several items or tests: A Monte Carlo simulation study MIZUMOTO, Atsushi University of Marketing and Distribution Sciences This paper
SEM: Structural Equation Modeling Nesselroade, SEM Bollen & Curran LGM: Latent Growth Model, McArdle,, LCM: Latent Curve Model, Meredith & Tisak, a LG
pp. ISSN Exploring the Patterns of Skill Development by Mixture Growth Modeling: Using the Batting Average Data on Professional Baseball Players Kazuaki SHIMIZU Abstract Reviewing latent growth modeling
03.Œk’ì
HRS KG NG-HRS NG-KG AIC Fama 1965 Mandelbrot Blattberg Gonedes t t Kariya, et. al. Nagahara ARCH EngleGARCH Bollerslev EGARCH Nelson GARCH Heynen, et. al. r n r n =σ n w n logσ n =α +βlogσ n 1 + v n w
149 (Newell [5]) Newell [5], [1], [1], [11] Li,Ryu, and Song [2], [11] Li,Ryu, and Song [2], [1] 1) 2) ( ) ( ) 3) T : 2 a : 3 a 1 :
![149 (Newell [5]) Newell [5], [1], [1], [11] Li,Ryu, and Song [2], [11] Li,Ryu, and Song [2], [1] 1) 2) ( ) ( ) 3) T : 2 a : 3 a 1 :](/thumbs/92/109497872.jpg "149 (Newell [5]) Newell [5], [1], [1], [11] Li,Ryu, and Song [2], [11] Li,Ryu, and Song [2], [1] 1) 2) ( ) ( ) 3) T : 2 a : 3 a 1 :")
Transactions of the Operations Research Society of Japan Vol. 58, 215, pp. 148 165 c ( 215 1 2 ; 215 9 3 ) 1) 2) :,,,,, 1. [9] 3 12 Darroch,Newell, and Morris [1] Mcneil [3] Miller [4] Newell [5, 6], [1]
kubostat2017b p.1 agenda I 2017 (b) probability distribution and maximum likelihood estimation :
kubostat2017b p.1 agenda I 2017 (b) probabilit distribution and maimum likelihood estimation kubo@ees.hokudai.ac.jp http://goo.gl/76c4i 2017 11 14 : 2017 11 07 15:43 1 : 2 3? 4 kubostat2017b (http://goo.gl/76c4i)
ヒストリカル法によるバリュー・アット・リスクの計測：市場価格変動の非定常性への実務的対応
VaR VaR VaR VaR GARCH E-mail : yoshitaka.andou@boj.or.jp VaR VaR LTCM VaR VaR VaR VaR VaR VaR VaR VaR t P(t) P(= P() P(t)) Pr[ P X] =, X t100 (1 )VaR VaR P100 P X X (1 ) VaR VaR VaR VaR VaR VaR VaR VaR
untitled
The Japanese Association for Behavior Analysis Newsletter, No. 35 The Japanese Association for Behavior Analysis Newsletter, No. 35 The Japanese Association for Behavior Analysis Newsletter, No. 35 Table
Hansen 1 2, Skinner 5, Augustinus 6, Harvey 7 Windle 8 Pels 9 1 Skinner 5 Augustinus 6 Pels 9 NL Harvey ML 11 NL
HANAOKA, Shinya 1 3 Hansen1, 2 1 2 3 Hansen 2 3 4 5 2 2.1 002 Vol.5 No.4 2003 Winter 3 4 2.2 Hansen 1 2, Skinner 5, Augustinus 6, Harvey 7 Windle 8 Pels 9 1 Skinner 5 Augustinus 6 Pels 9 NL Harvey 10 2.3
公務員倫理問題への新アプローチ
OECD CPI CPI CPI CPI CPI CPI / GDP / / / /.............................. Transparency International Corruption Perception Index CPI CPI 30 25 20 15 10 5 0 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
012 27-28 29 3 3 2 2 19 29 3 1 2 27-28,, 5 19 5 1 275 7,643 1 1 2 3 1 2 Class size Motivation -0.016 p =.036 1 0 2 Student level (Level 1) Class level (Level 2) Item 3 Item 13 Item 23 Item 33 Item 43
yamadaiR(cEFA).pdf
R 2012/10/05 Kosugi,E.Koji (Yamadai.R) Categorical Factor Analysis by using R 2012/10/05 1 / 9 Why we use... 3 5 Kosugi,E.Koji (Yamadai.R) Categorical Factor Analysis by using R 2012/10/05 2 / 9 FA vs
Attendance Demand for J-League õ Shinsuke KAWAI* and Takeo HIRATA* Abstract The purpose of this study was to clarify the variables determining the attendance in J-league matches, using the 2,699 J-league
橡表紙参照.PDF
CIRJE-J-58 X-12-ARIMA 2000 : 2001 6 How to use X-12-ARIMA2000 when you must: A Case Study of Hojinkigyo-Tokei Naoto Kunitomo Faculty of Economics, The University of Tokyo Abstract: We illustrate how to
2 (S, C, R, p, q, S, C, ML ) S = {s 1, s 2,..., s n } C = {c 1, c 2,..., c m } n = S m = C R = {r 1, r 2,...} r r 2 C \ p = (p r ) r R q = (q r ) r R
RF-004 Hashimoto Naoyuki Suguru Ueda Atsushi Iwasaki Yosuke Yasuda Makoto Yokoo 1 [10] ( ). ( ) 1 ( ) 3 4 3 4 = 12 deferred acceptance (DA) [3, 7] [5] ( ) NP serial dictatorship with regional quotas (SDRQ)
1 IDC Wo rldwide Business Analytics Technology and Services 2013-2017 Forecast 2 24 http://www.soumu.go.jp/johotsusintokei/whitepaper/ja/h24/pdf/n2010000.pdf 3 Manyika, J., Chui, M., Brown, B., Bughin,
Beyer, B. K. 1985 Critical thinking : What is it? Social Education, 49, 270-276. Ennis, R. H. 1962 A concept of critical thinking : A proposed basis for research in the teaching and evaluation of critical
パーソナリティ研究 2005 第13巻 第2号 170–182
2005 13 2 170 182 2005 1) I 23 567 8 3 6 1701 59 13 II 5 3 6 224 8.93.46.85 814 IRT III 3 38 3 35 3 2002 1) 2004 (1999) Buss & Perry (1992) 29 16 45 1125 7 38.40.40 3 6 (BAQ) BAQ (physical aggression)
untitled
2 : n =1, 2,, 10000 0.5125 0.51 0.5075 0.505 0.5025 0.5 0.4975 0.495 0 2000 4000 6000 8000 10000 2 weak law of large numbers 1. X 1,X 2,,X n 2. µ = E(X i ),i=1, 2,,n 3. σi 2 = V (X i ) σ 2,i=1, 2,,n ɛ>0
Adult Attachment Projective AAP PARS PARS PARS PARS Table
PARS PARS PARS PARS IWM IWM SATSAT Adult Attachment Projective AAP PARS PARS PARS PARS Table PARS PARS PARS PARS PARS AAP George, West, & Pettem Bowlby Bowlby George et al.,, Pp. - Geroge & West, PARS
3. ( 1 ) Linear Congruential Generator:LCG 6) (Mersenne Twister:MT ), L 1 ( 2 ) 4 4 G (i,j) < G > < G 2 > < G > 2 g (ij) i= L j= N
RMT 1 1 1 N L Q=L/N (RMT), RMT,,,., Box-Muller, 3.,. Testing Randomness by Means of RMT Formula Xin Yang, 1 Ryota Itoi 1 and Mieko Tanaka-Yamawaki 1 Random matrix theory derives, at the limit of both dimension
<30315F985F95B65F90B490852E696E6464>
Modeling for Change by Latent Difference Score Model: Adapting Process of the Student of Freshman at Half Year Intervals Kazuaki SHIMIZU and Norihiro MIHO Abstract The purpose of this paper is to present
The Japanese Journal of Psychology 2002, Vol. 73, No. 5, 405-411 Black sheep effect and ingroup favoritism in social identity perspective Chrtose Oishi and Fujio Yoshida (Institute of Psychology, University
k2 ( :35 ) ( k2) (GLM) web web 1 :
2012 11 01 k2 (2012-10-26 16:35 ) 1 6 2 (2012 11 01 k2) (GLM) kubo@ees.hokudai.ac.jp web http://goo.gl/wijx2 web http://goo.gl/ufq2 1 : 2 2 4 3 7 4 9 5 : 11 5.1................... 13 6 14 6.1......................
Newgarten, BL., Havighrst, RJ., & Tobin, S.Life Satisfaction Index-A LSIDiener. E.,Emmons,R.A.,Larsen,R.J.,&Griffin,S. The Satisfaction With Life Scal
青年期における人生に対する 積極的態度に関する研究 KJ 法による検討と尺度の構成を中心として 海老根 理 絵 臨床心理学コース The research of the positive attitude toward life in adolescence Rie EBINE The purpose of this study is to assess qualitatively the structure
P /fi¡ficfiNŒç
implicit memory levels of processing Craik Lockhart 1972 1988 cf. 1988 1 1980 1980 1 explicit memory implicit memory e.g., Graf & Schacter, 1985; Schacter, 1987 2001 priming direct priming effect 2 1 2
The Japanese Journal of Experimental Social Psychology. 2002, Vol. 41, No. 2, 155-164 V. 1986 An introduction to human memory. Routledge & Kegan Paul.) Hay, D. C., & Young, A. W. 1982 The human
untitled
18 1 2,000,000 2,000,000 2007 2 2 2008 3 31 (1) 6 JCOSSAR 2007pp.57-642007.6. LCC (1) (2) 2 10mm 1020 14 12 10 8 6 4 40,50,60 2 0 1998 27.5 1995 1960 40 1) 2) 3) LCC LCC LCC 1 1) Vol.42No.5pp.29-322004.5.
A5 PDF.pwd
Average Treatment Effect; ATE attributes Randomized Factorial Survey Experiment; RFSE cues ATE ATE Hainmueller et al. 2014 Average Marginal Component Effect ATE 67 4 2017 2 845 , ;, ATE, ;, ;, W 846 67
4.9 Hausman Test Time Fixed Effects Model vs Time Random Effects Model Two-way Fixed Effects Model
1 EViews 5 2007 7 11 2010 5 17 1 ( ) 3 1.1........................................... 4 1.2................................... 9 2 11 3 14 3.1 Pooled OLS.............................................. 14
CMCの社会的ネットワークを介した社会的スキルと孤独感との関連性
1 / 29 CMC [ ] CMC 1)2) (The effect of social skills on loneliness through mediation of CMC social networks) [ ] (Tasuku IGARASHI) [ ] (Graduate School of Education and Human Development, Nagoya University)
カルマンフィルターによるベータ推定（ ）
β TOPIX 1 22 β β smoothness priors (the Capital Asset Pricing Model, CAPM) CAPM 1 β β β β smoothness priors :,,. E-mail: koiti@ism.ac.jp., 104 1 TOPIX β Z i = β i Z m + α i (1) Z i Z m α i α i β i (the
k3 ( :07 ) 2 (A) k = 1 (B) k = 7 y x x 1 (k2)?? x y (A) GLM (k
2012 11 01 k3 (2012-10-24 14:07 ) 1 6 3 (2012 11 01 k3) kubo@ees.hokudai.ac.jp web http://goo.gl/wijx2 web http://goo.gl/ufq2 1 3 2 : 4 3 AIC 6 4 7 5 8 6 : 9 7 11 8 12 8.1 (1)........ 13 8.2 (2) χ 2....................
kubostat2018d p.2 :? bod size x and fertilization f change seed number? : a statistical model for this example? i response variable seed number : { i
kubostat2018d p.1 I 2018 (d) model selection and kubo@ees.hokudai.ac.jp http://goo.gl/76c4i 2018 06 25 : 2018 06 21 17:45 1 2 3 4 :? AIC : deviance model selection misunderstanding kubostat2018d (http://goo.gl/76c4i)
AR(1) y t = φy t 1 + ɛ t, ɛ t N(0, σ 2 ) 1. Mean of y t given y t 1, y t 2, E(y t y t 1, y t 2, ) = φy t 1 2. Variance of y t given y t 1, y t
87 6.1 AR(1) y t = φy t 1 + ɛ t, ɛ t N(0, σ 2 ) 1. Mean of y t given y t 1, y t 2, E(y t y t 1, y t 2, ) = φy t 1 2. Variance of y t given y t 1, y t 2, V(y t y t 1, y t 2, ) = σ 2 3. Thus, y t y t 1,
Microsoft Word - News 18 本文.doc
Argonauta 18: 17 30 (2010) 2007 1971 Cohen et al. 2003 A, B, C X, Y, Z 17 error error 1 0 1 1 X Y 1981 i) ii) 0 18 iii) iv) Yi = 0 + 1 X1i + 2 X2i + + p Xpi + i Xp pxpi + i i i Xp i Xp i 2 X Y 0 Xi Xi
浜松医科大学紀要
On the Statistical Bias Found in the Horse Racing Data (1) Akio NODA Mathematics Abstract: The purpose of the present paper is to report what type of statistical bias the author has found in the horse
5 Armitage x 1,, x n y i = 10x i + 3 y i = log x i {x i } {y i } 1.2 n i i x ij i j y ij, z ij i j 2 1 y = a x + b ( cm) x ij (i j )
5 Armitage. x,, x n y i = 0x i + 3 y i = log x i x i y i.2 n i i x ij i j y ij, z ij i j 2 y = a x + b 2 2. ( cm) x ij (i j ) (i) x, x 2 σ 2 x,, σ 2 x,2 σ x,, σ x,2 t t x * (ii) (i) m y ij = x ij /00 y
23_02.dvi
Vol. 2 No. 2 10 21 (Mar. 2009) 1 1 1 Effect of Overconfidencial Investor to Stock Market Behaviour Ryota Inaishi, 1 Fei Zhai 1 and Eisuke Kita 1 Recently, the behavioral finance theory has been interested
J. JILA 64 (5), 2001
Comparison of the Value of Outdoor Recreation: A Case Study Applying Travel Cost Method and Contingent Valuation Method Yasushi SHOJI J. JILA 64 (5), 2001 J. JILA 64 (5), 2001 2) Trice, A. H. and Wood,
教育社会学会（180903d）
2018/09/03 70 at teruki.sanada.s8@dc.tohoku.ac.jp Outline of this talk 1 Introduction 2 3 4 5 6 1 1 Introduction 1970 18/02/26 17/07/29 2 1 Introduction U 14000 12000 10000 8000 6000 4000 2000 0 H18 H19
3_1.dvi
Vol. 50 No. 3 1144 1155 (Mar. 2009) 1 1, 1 1 1 1, 2 1 source code review was conducted at first, then, unit testing, integration testing, and system testing are done. Results of source code review may
10 27 1 9 22 25 11 Gilovich et al., 1985, p.313 Gilovich et al. 1985 Adams, 1992; Albright, 1993; Koehler and Conley, 2003; Clark, 2005a, 2005b Gilovi
9 1 2 Process of Streaks in the volleyball game and game situation Yusuke Asai 1 and Masato Sagawa 2 Abstract The purpose of this study was investigation of process of Streaks in the volleyball game and
,.,.,,. [15],.,.,,., 2003 3 2006 2 3. 2003 3 2004 2 2004 3 2005 2, 1., 2005 3 2006 2, 1., 1,., 1,,., 1. i
![,.,.,,. [15],.,.,,., 2003 3 2006 2 3. 2003 3 2004 2 2004 3 2005 2, 1., 2005 3 2006 2, 1., 1,., 1,,., 1. i](/thumbs/41/22289268.jpg ",.,.,,. [15],.,.,,., 2003 3 2006 2 3. 2003 3 2004 2 2004 3 2005 2, 1., 2005 3 2006 2, 1., 1,., 1,,., 1. i")
200520866 ( ) 19 1 ,.,.,,. [15],.,.,,., 2003 3 2006 2 3. 2003 3 2004 2 2004 3 2005 2, 1., 2005 3 2006 2, 1., 1,., 1,,., 1. i 1 1 1.1..................................... 1 1.2...................................
仏大 社会学部論集４７号（Ｐ）／６．山口
47 2008 9 1 item reliability 1 2 Carmines & Zeller 1979 α 2 2 Knowles 1988Knowles 1988 4 1 Knowles 1988 1 30 1 30 1 30 4 120 30120 30 Z 1 30 r.510 3 r.366 r.370 r.350 Knowles 1992 MMPIKnowles et al. 1992Knowles
(pdf) (cdf) Matlab χ ( ) F t
(, ) (univariate) (bivariate) (multi-variate) Matlab Octave Matlab Matlab/Octave --...............3. (pdf) (cdf)...3.4....4.5....4.6....7.7. Matlab...8.7.....9.7.. χ ( )...0.7.3.....7.4. F....7.5. t-...3.8....4.8.....4.8.....5.8.3....6.8.4....8.8.5....8.8.6....8.9....9.9.....9.9.....0.9.3....0.9.4.....9.5.....0....3
untitled
c 645 2 1. GM 1959 Lindsey [1] 1960 Howard [2] Howard 1 25 (Markov Decision Process) 3 3 2 3 +1=25 9 Bellman [3] 1 Bellman 1 k 980 8576 27 1 015 0055 84 4 1977 D Esopo and Lefkowitz [4] 1 (SI) Cover and
Stata 11 Stata ROC whitepaper mwp anova/oneway 3 mwp-042 kwallis Kruskal Wallis 28 mwp-045 ranksum/median / 31 mwp-047 roctab/roccomp ROC 34 mwp-050 s
BR003 Stata 11 Stata ROC whitepaper mwp anova/oneway 3 mwp-042 kwallis Kruskal Wallis 28 mwp-045 ranksum/median / 31 mwp-047 roctab/roccomp ROC 34 mwp-050 sampsi 47 mwp-044 sdtest 54 mwp-043 signrank/signtest
52 Stringer 3 E. B. Taylor 3 2 2 1 23 1 Hofstede (1997) (1991)O Reilly et. al (1991)Payne & Phersey (1971) Litwin & Stringer (1974)Likert (1967) 16 1
Bulletin of Toyohashi Sozo College 2001, No. 5, 51 65 51 3 3 1 G. A. F. ForhandH. Gilmer 2 C. H. Litwin R. A. 52 Stringer 3 E. B. Taylor 3 2 2 1 23 1 Hofstede (1997) (1991)O Reilly et. al (1991)Payne &
(’Ó)”R
PAC Facework from the Perspectives of Interactions between Members: A Case Study of a Japanese Language Classroom by PAC analysis YOKOMIZO Tamaki The purpose of this study is to investigate how facework
And Business
Discussion Papers In Economics And Business Discussion Paper 03-06 Graduate School of Economics and Osaka School of International Public Policy (OSIPP) Osaka University, Toyonaka, Osaka 560-0043, JAPAN
082_rev2_utf8.pdf
3 1. 2. 3. 4. 5. 1 3 3 3 2008 3 2008 2008 3 2008 2008, 1 5 Lo and MacKinlay (1990a) de Jong and Nijman (1997) Cohen et al. (1983) Lo and MacKinlay (1990a b) Cohen et al. (1983) de Jong and Nijman (1997)
56 56 The Development of Preschool Children s Views About Conflict Resolution With Peers : Diversity of changes from five-year-olds to six-year-olds Y
56 56 The Development of Preschool Children s Views About Conflict Resolution With Peers : Diversity of changes from five-year-olds to six-year-olds Yukari KUBO 311615 1 1 1 97 43-2 2005 Rubin, Bukowski,
Japanese Journal of Applied Psychology
Japanese Journal of Applied Psychology 2018, Vol. 43, No. 3, 256 266 1 * ** Factors of Interest in Young Children among University Students: The Influences of Contact Experience with Infants, Internal
IPSJ SIG Technical Report Vol.2017-SLP-115 No /2/18 1,a) 1 1,2 Sakriani Sakti [1][2] [3][4] [5][6][7] [8] [9] 1 Nara Institute of Scie
![IPSJ SIG Technical Report Vol.2017-SLP-115 No /2/18 1,a) 1 1,2 Sakriani Sakti [1][2] [3][4] [5][6][7] [8] [9] 1 Nara Institute of Scie](/thumbs/104/162724895.jpg "IPSJ SIG Technical Report Vol.2017-SLP-115 No /2/18 1,a) 1 1,2 Sakriani Sakti [1][2] [3][4] [5][6][7] [8] [9] 1 Nara Institute of Scie")
1,a) 1 1,2 Sakriani Sakti 1 1 1 1. [1][2] [3][4] [5][6][7] [8] [9] 1 Nara Institute of Science and Technology 2 Japan Science and Technology Agency a) ishikawa.yoko.io5@is.naist.jp 2. 1 Belief-Desire theory
LHC-ATLAS Hà WWà lνlν A A A A A A
LHC-ATLAS Hà WWà lνlν A A A A A A 2011 1 Introduction 1fb -1 results and physics motivation -- ATLAS combined results with 1 fb -1 ZZà llnunu WWà lnulnu ZZà llll WWà lnuqq ATLAS official ATLAS 200-300
& 3 3 ' ' (., (Pixel), (Light Intensity) (Random Variable). (Joint Probability). V., V = {,,, V }. i x i x = (x, x,, x V ) T. x i i (State Variable),
.... Deeping and Expansion of Large-Scale Random Fields and Probabilistic Image Processing Kazuyuki Tanaka The mathematical frameworks of probabilistic image processing are formulated by means of Markov
kenkyujo_kiyo_09.ren
立正大学心理学研究所紀要 第９号 (2011) 付表１ 94 F p F p F p F p F P T F P T F P T F P T Neuron Evolutionary Psychology Behavioral and Brain Sciences Journal of Personality and Social Psychology Journal of Personality
新製品開発プロジェクトの評価手法
CIRJE-J-60 2001 8 A note on new product project selection model: Empirical analysis in chemical industry Kenichi KuwashimaUniversity of Tokyo Junichi TomitaUniversity of Tokyo August, 2001 Abstract By
Ishi
Ishi HPhttp: // www.mof.go.jp / jouhou / syuzei / siryou /.htm.. or ERTA, TRA ERTA Economic Recovery Tax Act TRA Tax Reform Act Mroz Triest Lindsey Burtless Navrati Lindsey Burtless Navrati CPS Current
Table 1 Means and standard deviations of topic familiarity for the topics used in the study Note. standard deviations are in parenthesis.
The Japanese Journal of Psychology 2000, Vol. 71, No, 4, 345-350 Contrast effects of background stimulus person on attitude similarity judgement and interpersonal attraction: A study of topic familiarity
60 Vol. 44 No. 1 2 準市場 化の制度的枠組み: 英国 教育改革法 1988 の例 Education Reform Act a School Performance Tables LEA 4 LEA LEA 3
Summer 08 59 I はじめに quasi market II III IV V 1 II 教育サービスにおける 準市場 1 教育サービスにおける 準市場 の意義 Education Reform Act 1988 1980 Local Education Authorities LEA Le Grand 1991 Glennerster 1991 3 1 2 3 2 60 Vol. 44
Editor-in-chief Vice-Editors-in-chief Standing Editors Editorial Board Koichi MIYOSHI Keiko NISHINO Shunichi FURUKAWA Hiromitsu MUTA Kiyoshi YAMAYA Ed
ISSN 1346-6151 The Japanese Journal of Evaluation Studies Vol. 6, No. 1, March 2006 The Japan Evaluation Society Editor-in-chief Vice-Editors-in-chief Standing Editors Editorial Board Koichi MIYOSHI Keiko
,, Poisson 3 3. t t y,, y n Nµ, σ 2 y i µ + ɛ i ɛ i N0, σ 2 E[y i ] µ * i y i x i y i α + βx i + ɛ i ɛ i N0, σ 2, α, β *3 y i E[y i ] α + βx i
![,, Poisson 3 3. t t y,, y n Nµ, σ 2 y i µ + ɛ i ɛ i N0, σ 2 E[y i ] µ * i y i x i y i α + βx i + ɛ i ɛ i N0, σ 2, α, β *3 y i E[y i ] α + βx i](/thumbs/87/95421301.jpg ",, Poisson 3 3. t t y,, y n Nµ, σ 2 y i µ + ɛ i ɛ i N0, σ 2 E[y i ] µ * i y i x i y i α + βx i + ɛ i ɛ i N0, σ 2, α, β *3 y i E[y i ] α + βx i")
Armitage.? SAS.2 µ, µ 2, µ 3 a, a 2, a 3 a µ + a 2 µ 2 + a 3 µ 3 µ, µ 2, µ 3 µ, µ 2, µ 3 log a, a 2, a 3 a µ + a 2 µ 2 + a 3 µ 3 µ, µ 2, µ 3 * 2 2. y t y y y Poisson y * ,, Poisson 3 3. t t y,, y n Nµ,
untitled
f c Human Capital: A Theoretical and Empirical Analysis, with Special Reference to Education The Scientific Analysis of Personality Emotional Intelligence: Why It Can Matter More than IQ Psychological
fiúŁÄ”s‘ê‡ÌŁª”U…−…X…N…v…„…~…A…•‡Ì ”s‘ê™´›ß…−…^†[…fiŠ‚ª›Âfl’«
2016/3/11 Realized Volatility RV 1 RV 1 Implied Volatility IV Volatility Risk Premium VRP 1 (Fama and French(1988) Campbell and Shiller(1988)) (Hodrick(1992)) (Lettau and Ludvigson (2001)) VRP (Bollerslev