Biometrika - Advance Access

On an internal method for deriving a summary measure

Cox, D. R. — 2008-09-29

Some preliminary comments are made about the reasons for combining component observations into composite or derived variables. A method for forming derived variables sensitive to specified changes in the underlying multivariate distribution is described and illustrated by an issue in a study of animal pathology.

Estimating the false discovery rate using the stochastic approximation algorithm

Liang, F., Zhang, J. — 2008-09-26

Testing of multiple hypotheses involves statistics that are strongly dependent in some applications, but most work on this subject is based on the assumption of independence. We propose a new method for estimating the false discovery rate of multiple hypothesis tests, in which the density of test scores is estimated parametrically by minimizing the Kullback–Leibler distance between the unknown density and its estimator using the stochastic approximation algorithm, and the false discovery rate is estimated using the ensemble averaging method. Our method is applicable under general dependence between test statistics. Numerical comparisons between our method and several competitors, conducted on simulated and real data examples, show that our method achieves more accurate control of the false discovery rate in almost all scenarios.

On the consequences of overstratification

De Stavola, B. L., Cox, D. R. — 2008-09-25

It is common, in particular in observational studies in epidemiology, to impose stratification to adjust for possible effects of age and other variables on the binary outcome of interest. Overstratification may lower the precision of the estimated effects of interest. Understratification risks bias. These issues are studied analytically. Asymptotic results show that loss of efficiency depends on the true effect and on a measure of the average imbalance across strata between exposed and unexposed individuals. Bias depends on the correlation between stratum-specific size imbalances and event rates in the unexposed. Approximate results are also given. An example is used.

Forecasting with the age-period-cohort model and the extended chain-ladder model

Kuang, D., Nielsen, B., Nielsen, J. P. — 2008-09-22

We consider forecasting from age-period-cohort models, as well as from the extended chain-ladder model. The parameters of these models are known only to be identified up to linear trends. Forecasts from such models may therefore depend on arbitrary linear trends. A condition for invariant forecasts is proposed. A number of standard forecast models are analyzed.

On consistency of Kendall's tau under censoring

Oakes, D. — 2008-09-17

Necessary and sufficient conditions for consistency of a simple estimator of Kendall's tau under bivariate censoring are presented. The results are extended to data subject to bivariate left truncation as well as right censoring.

Identification of the age-period-cohort model and the extended chain-ladder model

Kuang, D., Nielsen, B., Nielsen, J. P. — 2008-09-15

We consider the identification problem that arises in the age-period-cohort models as well as in the extended chain-ladder model. We propose a canonical parameterization based on the accelerations of the trends in the three factors. This parameterization is exactly identified and eases interpretation, estimation and forecasting. The canonical parameterization is applied to a class of index sets which have trapezoidal shapes, including various Lexis diagrams and the insurance-reserving triangles.