Model-checking techniques for stratified case-control studies

Statistics in Medicine

Volumn 24, Issue 2, 2005, Pages 229-247

  Arbogast, Patrick G ^a   Lin, D Y ^b  

^a VANDERBILT UNIVERSITY MEDICAL CENTER   (United States)

^b IL   (United States)

Author keywords

Goodness of fit; Link function; Logistic regression; Model misspecification; Regression diagnostic; Residual

Indexed keywords

ANALYTIC METHOD; ARTICLE; CASE CONTROL STUDY; ESOPHAGUS CANCER; HUMAN; LOGISTIC REGRESSION ANALYSIS; MONTE CARLO METHOD; NORMAL DISTRIBUTION; STATISTICAL MODEL;

ADULT; AGE FACTORS; AGED; AGED, 80 AND OVER; ALCOHOL DRINKING; CASE-CONTROL STUDIES; COMPUTER SIMULATION; ESOPHAGEAL NEOPLASMS; HUMANS; LOGISTIC MODELS; MALE; MIDDLE AGED; MODELS, BIOLOGICAL; MONTE CARLO METHOD; SMOKING;

EID: 12344301400     PISSN: 02776715     EISSN: None     Source Type: Journal    
DOI: 10.1002/sim.1932     Document Type: Article

References (21)

1. Prentice RL, Pyke R. Logistic disease incidence models and case-control studies. Biometrika 1979; 66: 403-411.
2. Hosmer DW, Hosmer T, Le Cessie S, Lemeshow S. A comparison of goodness-of-fit tests for the logistic regression model. Statistics in Medicine 1997; 16:965-980.
3. Pregibon D. Logistic regression diagnostics. The Annals of Statistics 1981; 9:705-724.
4. Hosmer DW, Lemeshow S. A goodness-of-fit test for the multiple logistic regression model. Communications in Statistics 1980; A10:1043-1069.
5. Osius G, Rojek D. Normal goodness-of-fit tests for multinomial models with large degrees-of-freedom. Journal of the American Statistical Association 1992; 87:1145-1152.
6. Stukel TA. Generalized logistic models. Journal of the American Statistical Association 1988; 83:426-431.
7. Hosmer DW, Lemeshow S. Applied Logistic Regression (2nd edn). Wiley: New York, 2000.
8. Qin J, Zhang B. A goodness-of-fit test for logistic regression models based on case-control data. Biometrika 1997; 84:609-618.
9. Zhang B. A chi-squared goodness-of-fit test for logistic regression models based on case-control data. Biometrika 1999; 86:531-539.
10. Breslow NE, Day NE. Statistical Methods in Cancer Research, vol. 1. The Analysis of Case-Control Studies. International Agency for Research on Cancer: Lyon, 1980.
11. Scott AJ, Wild CJ. Fitting logistic models under case-control or choice-based sampling. Journal of the Royal Statistical Society, Series B 1986; 48:170-182.
12. McCullagh P, Nelder JA. Generalized Linear Models (2nd edn). Chapman & Hall: London, 1989.
13. Su JQ, Wei LJ. A lack-of-fit test for the mean function in a generalized linear model. Journal of the American Statistical Association 1991; 86:420-426.
14. Lin DY, Wei LJ, Ying Z. Model-checking techniques based on cumulative residuals. Biometrics 2002; 58:1-12.
15. Lin DY, Wei LJ, Ying Z. Checking the Cox model with cumulative sums of martingale-based residuals. Biometrika 1993; 80:557-572.
16. Spiekerman CF, Lin DY. Checking the marginal Cox model for correlated failure time data. Biometrika 1996; 83:143-156.
17. Royston P, Altman DG. Regression using fractional polynomials of continuous covariates: parsimonious parametric modelling. Applied Statistics, 1994; 43:429-467.
18. Royston P, Ambler G, Sauerbrei W. The use of fractional polynomials to model continuous risk variables in epidemiology. International Journal of Epidemiology 1999; 28:964-974.
19. Pulkstnis E, Robinson TJ. Two goodness-of-fit tests for logistic regression models with continuous covariates. Statistics in Medicine 2002; 21:79-93.
20. Pollard D. Empirical Processes: Theory and Applications Institute of Mathematical Statistics: Hayward, 1990.
21. Billias Y, Gu M, Ying Z. Towards a general asymptotic theory for Cox model with staggered entry. The Annals of Statistics 1997; 25:662-682.