Dynamic modelling in a study of surgical error management

Statistics in Medicine

Volumn 26, Issue 28, 2007, Pages 5189-5202

  Solis Trapala, I L ^a   Carthey, J ^b   Farewell, Vern T ^c   de Leval, M R ^d  

^a LANCASTER UNIVERSITY   (United Kingdom)

^b NATIONAL PATIENT SAFETY AGENCY   (United Kingdom)

^c MRC BIOSTATISTICS UNIT   (United Kingdom)

^d International Congenital Cardiac Centre   (United Kingdom)

Author keywords

Arterial switch operation; Dynamic conditional logistic regression; Dynamic logistic regression with random effects; Surgical error management

Indexed keywords

ARTICLE; BIOSTATISTICS; CONGENITAL HEART DISEASE; CONTROLLED STUDY; DYNAMICS; FEMALE; HEART SURGERY; HUMAN; LOGISTIC REGRESSION ANALYSIS; MALE; PROBABILITY; STATISTICAL MODEL; SURGICAL ERROR;

CARDIAC SURGICAL PROCEDURES; FEMALE; GREAT BRITAIN; HUMANS; INFANT, NEWBORN; INTERDISCIPLINARY COMMUNICATION; LOGISTIC MODELS; MALE; MEDICAL ERRORS; MODELS, STATISTICAL; OUTCOME ASSESSMENT (HEALTH CARE); PATIENT CARE TEAM; PROBABILITY; TRANSPOSITION OF GREAT VESSELS;

EID: 36348959689     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.2886     Document Type: Article

References (29)

1. de Leval MR, Carthey J, Wright DJ, Farewell VT, Reason JT. Human factors and surgical outcomes: a multi-center study. Journal of Thoracic Cardiovascular Surgery 2000; 119:661-672.
2. Carthey J, de Leval MR, Reason JT, Farewell VT, Wright DJ. Human factors research in cardiac surgery: opportunities and pitfalls. Clinical Risk 2001; 7:85-90.
3. Reason JT. Human Error. Cambridge University Press: Cambridge, MA, 1990.
4. Bonney GE. Logistic regression for dependent binary observations. Biometrics 1987; 43:951-973.
5. Ware JH, Lipsitz SR, Speizer FE. Issues in the analysis of repeated categorical outcomes. Statistics in Medicine 1988; 7:95-107.
6. Zeger SL, Qaqish B. Markov regression models for time series: a quasi-likelihood approach. Biometrics 1988; 44:1019-1031.
7. Kaufmann H, Regression models for nonstationary categorical time series: asymptotic estimation theory. Annals of Statistics 1987; 15:79-98.
8. Aalen OO, Fosen J, Weedon-Fekjær H, Borgan Ø, Husebye E. Dynamic analysis of multivariate failure time data. Biometrics 2004; 60:764-773.
9. Cox DR. The regression analysis of binary sequences (with discussion). Journal of the Royal Statistical Society, Series B 1958; 20:215-242.
10. Haldane JBS, Smith CAB. A simple exact test for birth order effect. Annals of Eugenics 1948; 14:117-124.
11. Cox DR. Partial likelihood. Biometrika 1975; 62:269-276.
12. Chambers EA, Cox DR. Discrimination between alternative binary response models. Biometrika 1967; 54:573-578.
13. Neuhaus JM, Hauck WW, Kalbfleisch JD. The effects of mixture distribution misspecification when fitting mixed-effects logistic models. Biometrika 1992; 79:755-762.
14. Neuhaus JM, Kalbfleisch JD, Hauck WW. Conditions for consistent estimation in mixed-effects models for binary matched-pairs data. The Canadian Journal of Statistics 1994; 22:139-148.
15. Neuhaus JM, Lesperance ML. Estimation efficiency in a binary mixed-effects model setting. Biometrika 1996; 83:441-446.
16. Crouchley R, Davies RB. A comparison of population average and random-effect models for the analysis of longitudinal count data with base-line information. Journal of the Royal Statistical Society, Series A 1999; 162:331-347.
17. Nerlove M. Essays in Panel Data Econometrics. Cambridge University Press: Cambridge, MA, 2002.
18. Bhargava A, Sargan JD. Estimating dynamic random effects models from panel data covering short time periods. Econometrica 1983; 51:1635-1659.
19. Cameron AC, Trivedi PK. Regression Analysis of Count Data. Cambridge University Press: Cambridge, MA, 1998.
20. Aitkin M, Alfo M. Longitudinal analysis of repeated binary data using autoregressive and random effect modelling. Statistical Modelling 2003; 3:291-303.
21. Alfo M, Aitkin M. Variance component models for longitudinal count data with baseline information: epilepsy data revisited. Statistical Computing 2006; 16:231-238.
22. Chamberlain G. Analysis of covariance with qualitative data. Review of Economic Studies 1980; 47:225-238.
23. Zhang D, Davidian M. Likelihood and conditional likelihood inference for generalized additive mixed models for cluster data. Journal of Multivariate Analysis 2004; 91:90-106.
24. Lin X, Zhang D. Inference in generalized additive mixed models by using smoothing splines. Journal of the Royal Statistical Society, Series B 1999; 61:381-400,
25. Hastie T, Tibshirani R. Generalized Additive Models. Chapman & Hall: London, 1990.
26. Cox DR. Regression models and life tables. Journal of the Royal Statistical Society, Series B 1972; 24:187-220.
27. Rabe-Hesketh S, Skrondal A, Pickles A. Maximum likelihood estimation of generalized linear models with covariate measurement error. The Stata Journal 2001; 1:1-26.
28. Liang K-Y, Zeger SL. Longitudinal data analysis using generalized linear models. Biometrika 1986; 73:13-22.
29. Stiratelli R, Laird N, Ware JH. Random-effects models for serial observations with binary response. Biometrics 1984; 40:961-971.