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## Longitudinal data analysis using generalized linear models”. (1986)

Venue: | Biometrika, |

Citations: | 1526 - 8 self |

### Citations

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Analysis of binary data.
- Cox, Snell
- 1990
(Show Context)
Citation Context ... expect it often will be. Modelling the marginal expectation and treating the correlation as a nuisance may be less appropriate when the time course of the outcome for each subject, e.g. growth, is of primary interest or when the correlation itself has scientific relevance. The random effects model for binary data discussed by Stiratelli, Laird & Ware (1984) can be extended to the generalized linear model family and is more appropriate for the study of growth. When the time dependence is central, models for the conditional distribution of yt given yt_1,yl_2> •••;2/i m a y be more appropriate. Cox (1970, p. 72) has proposed such a model for binary outcomes. Korn & Whittemore (1979) have applied this model to air pollution data. The examples in §4 provide several alternative methods for analysing longitudinal data sets. The method in Example 1, which includes the independence estimating equation as a special case, requires the fewest assumptions. Only the regression specification must be correct to obtain consistent estimates of/5 and var(/?). In §5, the independence estimator was shown to have high efficiency when the correlation is moderate in a simple situation with binary outcomes, Table ... |

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