Handling initial conditions and endogenous covariates in dynamic/transition models for binary data with unobserved heterogeneity

Journal of the Royal Statistical Society. Series C: Applied Statistics

Volumn 63, Issue 2, 2014, Pages 211-237

  Skrondal, Anders ^a   Rabe Hesketh, Sophia ^b,c  

^a NORWEGIAN INSTITUTE OF PUBLIC HEALTH   (Norway)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c UNIVERSITY OF LONDON   (United Kingdom)

Author keywords

Auto regressive model; Dynamic model; Endogeneity; Gllamm; Initial conditions; Panel data; State dependence; Transition model; Unobserved confounding

Indexed keywords

EID: 84894470450     PISSN: 00359254     EISSN: 14679876     Source Type: Journal    
DOI: 10.1111/rssc.12023     Document Type: Article

References (72)

1. Aitkin, Mand Alfo, M(1998) Regression models for binary longitudinal responsesStatistComput., 8, 289-307
2. Aitkin, Mand Alfo, M(2003) Longitudinal analysis of repeated binary data using autoregressive and random effect modellingStatistModllng, 3, 291-303
3. Akay, A(2012) Finite-sample comparison of alternative methods for estimating dynamic panel data modelsJApplEconmetr., 27, 1189-1204
4. Albert, PSand Follmann, DA(2003) A random effects transition model for longitudinal binary data with informative missingnessStatistNeerland., 57, 100-111
5. Albert, PSand Follmann, DA(2007) Random effects and latent processes approaches for analyzing binary longitudinal data with missingness: a comparison of approaches using opiate clinical trial dataStatistMethMedRes., 16, 417-439
6. An, SS., Bai, TR., Bates, JHT., Black, JL., Brown, RH., Brusasco, V., Chitano, P., Deng, L., Dowell, M., Eidelman, DH., Fabry, B., Fairbank, NJ., Ford, LE., Fredberg, JJ., Gerthoffer, WT., Gilbert, SH., Gosens, R., Gunst, SJ., Halayko, AJ., Ingram, RH., Irvin, CG., James, AL., Janssen, LJ., King, GG., Knight, DA., Lauzon, AM., Lakser, OJ., Ludwig, MS., Lutchen, KR., Maksym, GN., Martin, JG., Mauad, T., McParland, BE., Mijailovich, SM., Mitchell, HW., Mitchell, RW., Mitzner, W., Murphy, TM., Par, PD., Pellegrino, R., Sanderson, MJ., Schellenberg, RR., Seow, CY., Silveira, PSP., Smith, PG., Solway, J., Stephens, NL., Sterk, PJ., Stewart, AG., Tang, DD., Tepper, RS., Tran, Tand Wang, L(2007) Airway smooth muscle dynamics: a common pathway of airway obstruction in asthmaEurRespJ., 29, 834-860
7. Anderson, TWand Hsiao, C(1982) Formulation and estimation of dynamic models using panel dataJEconmetr., 18, 47-82
8. Arellano, Mand Bond, S(1991) Some tests of specification for panel data: Monte Carlo evidence and an application to employment equationsRevEconStud., 58, 277-297
9. Arulampalam, Wand Stewart, MB(2009) Simplified implementation of the Heckman estimator of the dynamic probit model and a comparison with alternative estimatorsOxfBullEconStatist., 71, 659-681
10. Bartolucci, Fand Nigro, V(2010) A dynamic model for binary panel data with unobserved heterogeneity admitting a n-consistent conditional estimatorEconometrica, 78, 719-733
11. Bates, GEand Neyman, J(1952) Contributions to the theory of accident proneness II: True or false contagionUnivCalifPublStatist., 1, 255-275
12. Bhargava, Aand Sargan, JD(1983) Estimating dynamic random effects models from panel data covering short time periodsEconometrica, 51, 1635-1659
13. Blundell, Rand Windmeijer, F(1997) Cluster effects and simultaneity in multilevel modelsHlth Econ., 6, 439-443
14. Bock, RDand Lieberman, M(1970) Fitting a response model for n dichotomously scored itemsPsychometrika, 33, 179-197
15. Bollen, KAand Curran, PJ(2004) Autoregressive latent trajectory (ALT) models: a synthesis of two traditionsSociolMethRes., 32, 336-383
16. Chamberlain, G(1980) Analysis of covariance with qualitative dataRevEconStud., 47, 225-238
17. Chamberlain, G(1982) Multivariate regression models for panel dataJEconmetr., 18, 5-46
18. Chamberlain, G(1984) Panel dataIn Handbook of Econometrics, volII (eds ZGriliches and MDIntriligator), pp1247-1318Amsterdam: North-Holland
19. Coleman, JS(1964) Models of Change and Response UncertaintyEnglewood Cliffs: Prentice Hall
20. Crouchley, Rand Davies, RB(2001) A comparison of GEE and random effects models for distinguishing heterogeneity, nonstationarity and state dependence in a collection of short binary event seriesStatistModllng, 1, 271-285
21. Davies, RBand Crouchley, R(1985) Control for omitted variables in the analysis of panel and other longitudinal dataGeogrAnal., 17, 1-15
22. Davies, RBand Pickles, A(1986) Accounting for omitted variables in a discrete time panel data model of residential mobilityQualQuant., 20, 219-233
23. Diggle, PJ., Heagerty, P., Liang, K.-Yand Zeger, SL(2002) Analysis of Longitudinal DataOxford: Oxford University Press
24. Dundas, Iand McKenzie, S(2006) Spirometry in the diagnosis of asthma in childrenCurrOpinPulmMed., 12, 28-33
25. Fahrmeir, Land Tutz, G(2001) Multivariate Statistical Modelling based on Generalized Linear Models, New York: Springer
26. Ferris, BG., Ware, JH., Berkey, CS., Dockery, DW., Spiro, Aand Speizer, FE(1985) Effects of passive smoking on health of childrenEnvironHlth Perspect., 62, 289-295
27. Fotouhi, AR(2005) The initial conditions problem in longitudinal binary process: a simulation studySimuln Modllng PractTheor., 13, 566-583
28. Francis, BJ., Stott, DNand Davies, RB(1996) SABRE: a Guide for Users, Version 3.1Lancaster: Lancaster University(Available from http://www.cas.lancs.ac.uk/software/sabre3.1/sabre.html.)
29. Fuhlbrigge, AL., Kitch, BT., Paltiel, AD., Kuntz, KM., Neumann, PJ., Dockery, DWand Weiss, ST(2001) FEV1 is associated with risk of asthma attacks in a pediatric populationJAllgy ClinImmun., 107, 61-67
30. Gilliland, FD., Li, Y.-Fand Peters, JM(2001) Effects of maternal smoking during pregnancy and environmental tobacco smoke on asthma and wheezing in childrenAmJRespCritCare Med., 163, 429-436
31. Hajivassiliou, VAand Ioannides, YM(2007) Unemployment and liquidity constraintsJApplEconmetr., 22, 479-510
32. Hasegawa, H(2009) Bayesian dynamic panel-ordered probit model and its application to subjective well-beingCommuns StatistSimuln Computn, 38, 1321-1347
33. Heagerty, PJand Kurland, BF(2001) Misspecified maximum likelihood estimates and generalized linear mixed modelsBiometrika, 88, 973-985
34. Heckman, JJ(1981a) The incidental parameters problem and the problem of initial conditions in estimating a discrete time - discrete data stochastic processIn Structural Analysis of Discrete Data with Econometric Applications (eds CFManski and DLMcFadden), pp179-195Cambridge: MIT Press
35. Heckman, JJ(1981b) Heterogeneity and state dependenceIn Studies in Labor Markets (edSRosen), pp91-139Chicago: University of Chicago Press
36. Heckman, JJ(1981c) Statistical models for discrete panel dataIn Structural Analysis of Discrete Data with Econometric Applications (eds CFManski and DLMcFadden), pp179-195Cambridge: MIT Press
37. Honoré, BEand Kyriazidou, E(2000) Panel data discrete choice models with lagged dependent variablesEconometrica, 68, 839-874
38. Hsiao, C(2002) Analysis of Panel Data, Cambridge: Cambridge University Press
39. Hyslop, DR(1999) State dependence, serial correlation and heterogeneity in intertemporal labor force participation of married womenEconometrica, 67, 1255-1294
40. Laird, NM(1978) Nonparametric maximum likelihood estimation of a mixing distributionJAmStatistAss., 73, 805-811
41. Lawal, B(2003) Categorical Data Analysis with SAS and SPSS ApplicationsMahwah: Erlbaum
42. Mandel, Mand Betensky, RA(2008) Estimating time-to-event from longitudinal ordinal data using random-effects Markov models: application to multiple sclerosis progressionBiostatistics, 9, 750-764
43. Michaud, P.-Cand Tatsiramos, K(2011) Fertility and female employment dynamics in Europe: the effect of using alternative econometric modeling assumptionsJApplEconmetr., 26, 641-668
44. Mundlak, Y(1978) On the pooling of time series and cross section dataEconometrica, 84, 69-85
45. Nafstad, P., Jaakkola, JJ., Hagen, JA., Zahlsen, Kand Magnus, P(1997) Hair nicotine concentrations in mothers and children in relation to parental smokingJExposAnalEnvironEpidem., 7, 235-239
46. Nerlove, M(1971) Further evidence on the estimation of dynamic economic relations from a time series of cross sectionsEconometrica, 39, 359-382
47. Neuhaus, JMand McCulloch, CM(2006) Separating between- and within-cluster covariate effects by using conditional and partitioning methodsJRStatistSocB, 68, 859-872
48. Ober, Cand Yao, T.-C(2011) The genetics of asthma and allergic disease: a 21st century perspectiveImmunRev., 242, 10-30
49. Orme, CD(2001) Two-step inference in dynamic non-linear panel data modelsTechnical ReportSchool of Economic Studies, University of Manchester, Manchester
50. Pudney, S(2008) The dynamics of perception: modelling subjective wellbeing in a short panelJRStatistSocA, 171, 21-40
51. Rabe-Hesketh, S., Pickles, Aand Skrondal, A(2003) Correcting for covariate measurement error in logistic regression using nonparametric maximum likelihood estimationStatistModllng, 3, 215-232
52. Rabe-Hesketh, Sand Skrondal, A(2001) Parameterization of multivariate random effects models for categorical dataBiometrics, 57, 1256-1264
53. Rabe-Hesketh, Sand Skrondal, A(2006) Multilevel modelling of complex survey dataJRStatistSocA, 169, 805-827
54. Rabe-Hesketh, Sand Skrondal, A(2012) Multilevel and Longitudinal Modeling using Stata, 3rd edn, volII, Categorical Responses, Counts, and SurvivalCollege Station: Stata Press
55. Rabe-Hesketh, Sand Skrondal, A(2013) Avoiding biased versions of Wooldridge's simple solution to the initial conditions problemEconLett., 120, 346-349
56. Rabe-Hesketh, S., Skrondal, Aand Pickles, A(2004a) Generalized multilevel structural equation modelingPsychometrika, 69, 167-190
57. Rabe-Hesketh, S., Skrondal, Aand author"Pickles, A(2004b) GLLAMM manualTechnical Report 160Division of Biostatistics, University of California, Berkeley(Available from http://www.bepress.com/ucbbiostat/paper160/.)
58. Rabe-Hesketh, S., Skrondal, Aand Pickles, A(2005) Maximum likelihood estimation of limited and discrete dependent variable models with nested random effectsJEconmetr., 128, 301-323
59. Rotnitzky, AGand Wypij, D(1994) A note on the bias of estimators with missing dataBiometrics, 50, 1163-1170
60. Skrondal, Aand Rabe-Hesketh, S(2004) Generalized Latent Variable Modeling: Multilevel, Longitudinal, and Structural Equation ModelsBoca Raton: Chapman and Hall-CRC
61. Snijders, TABand Berkhof, J(2008) Diagnostic checks for multilevel modelsIn Handbook of Multilevel Analysis (eds Jde Leeuw and EMeijer), pp141-175New York: Springer
62. Song, C., Kuo, L., Derby, CA., Lipton, RBand Hall, CB(2011) Multi-stage transitional models with random effects and their application to the Einstein aging studyBiometrJ., 53, 938-955
63. Speizer, FE(1990) Asthma and persistent wheeze in the Harvard Six Cities StudyChest, 98, suppl., 191S-195S
64. Stein, RT., Sherill, D., Morgan, WJ., Holberg, CJ., Halonen, M., Taussig, LM., Wright, ALand Martinez, FD(1999) Respiratory syncytial virus in early life and risk of wheeze and allergy by age 13 yearsLancet, 354, 541-545
65. Stewart, MB(2006) Maximum simulated likelihood estimation of random-effects dynamic probit models with autocorrelated errorsStataJ., 6, 256-272
66. Sutradhar, BCand Farrell, PJ(2007) On optimal lag 1 dependence estimation for dynamic binary models with application to asthma dataSankyha B, 69, 448-467
67. Train, KE(2009) Discrete Choice Methods with Simulation, Cambridge: Cambridge University Press
68. Verbeke, Gand Molenberghs, G(2000) Linear Mixed Models for Longitudinal DataNew York: Springer
69. Ware, JH., Dockery, DW., Spiro, A., Speizer, FEand Ferris, BG(1984) Passive smoking, gas cooking and respiratory health in children living in six citiesAmRevRespDis., 129, 366-374
70. White, H(1982) Maximum likelihood estimation of misspecified modelsEconometrica, 50, 1-25
71. Wooldridge, JM(2005) Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneityJApplEconmetr., 20, 39-54
72. Wooldridge, JM(2010) Econometric Analysis of Cross Section and Panel Data, Cambridge: MIT Press