Case–control studies with complex sampling

The use of complex sampling designs in population-based case–control studies is becoming more common, particularly for sampling the control population. This is prompted by all the usual cost and logistical benefits that are conferred by multistage sampling. Complex sampling has often been ignored in analysis but, with the advent of packages like SUDAAN, survey-weighted analyses that take account of the sample design can be carried out routinely. This paper explores this approach and more efficient alternatives, which can also be implemented by using readily available software.     

Consistent Estimation of the Structural Distribution Function

Motivated by problems in linguistics we consider a multinomial random vector for which the number of cells N is not much smaller than the sum of the cell frequencies, i.e. the sample size n . The distribution function of the uniform distribution on the set of all cell probabilities multiplied by N is called the structural distribution function of the cell probabilities. Conditions are given that guarantee that the structural distribution function can be estimated consistently as n increases indefinitely although n / N does not. The natural estimator is inconsistent and we prove consistency of essentially two alternative estimators.     

Profile upper Confidence Limits from Discrete Data

When the data are discrete, standard approximate confidence limits often have coverage well below nominal for some parameter values. While ad hoc adjustments may largely solve this problem for particular cases, Kabaila & Lloyd (1997) gave a more systematic method of adjustment which leads to tight upper limits, which have coverage which is never below nominal and are as small as possible within a particular class. However, their computation for all but the simplest models is infeasible. This paper suggests modifying tight upper limits by an initial replacement of the unknown nuisance parameter vector by its profile maximum likelihood estimator. While the resulting limits no longer possess the optimal properties of tight limits exactly, the paper presents both numerical and theoretical evidence that the resulting coverage function is close to optimal. Moreover these profile upper limits are much (possibly many orders of magnitude) easier to compute than tight upper limits.     

Using Bayesian graphical models to model biases in observational studies and to combine multiple sources of data: application to low birth weight and water disinfection by-products

Summary.  Data in the social, behavioural and health sciences frequently come from observational studies instead of controlled experiments. In addition to random errors, observational data typically contain additional sources of uncertainty such as missing values, unmeasured confounders and selection biases. Also, the research question is often different from that which a particular source of data was designed to answer, and so not all relevant variables are measured. As a result, multiple sources of data are often necessary to identify the biases and to inform about different aspects of the research question. Bayesian graphical models provide a coherent way to connect a series of local submodels, based on different data sets, into a global unified analysis. We present a unified modelling framework that will account for multiple biases simultaneously and give more accurate parameter estimates than standard approaches. We illustrate our approach by analysing data from a study of water disinfection by-products and adverse birth outcomes in the UK.     

Preserving Open Access

Abstract

Libraries have an established track record of preserving the scholarly record, but this stewardship role has generally been exercised over materials the library has purchased or otherwise acquired. With open access publishing, the library’s role in preservation is less certain, as libraries may facilitate access to a wide array of freely accessible materials without ever obtaining any copies. Additionally, the open access landscape includes many small noncommercial publishers with limited resources that may not be able to invest in long term preservation and access. In this column, Courtney McAllister, Electronic Resources Librarian at Lillian Goldman Law Library, Yale University, discusses preservation concerns and strategies for open access publications and how libraries may be affected by unstable or unpredictable long-term access.     

Serials spoken here: reports of conferences,institutes, and seminars

Abstract

Reports on the Ohio Valley Group of Technical Services Librarians (OVGTSL) Annual Conference, the April 2004 New England Technical Services Librarians (NETSL) Conference, the 2004 Acquisitions Institute at Timberline Lodge, and the 2004 Conference of the North American Serials Interest Group (NASIG).

Reports are from four conferences held in various parts of the United States and cover a wide range of topics. The Ohio Valley Group of Technical Services Librarians program emphasized the relationship between technical and public services. Education, both formal and continuing, was the theme for the New England Technical Services Librarians. Timberline Lodge hosted another Acquisitions Institute featuring sessions on new discoveries. The report on the 2004 North American Serials Group Annual Conference allows Conference Student Grant Award winner Chris Brady to include some personal reflections along with summaries of the sessions he attended.     

Performance of standard imputation methods for missing quality of life data as covariate in survival analysis based on simulations from the International Breast Cancer Study Group Trials VI and VII*

Abstract

Imputation methods for missing data on a time-dependent variable within time-dependent Cox models are investigated in a simulation study. Quality of life (QoL) assessments were removed from the complete simulated datasets, which have a positive relationship between QoL and disease-free survival (DFS) and delayed chemotherapy and DFS, by missing at random and missing not at random (MNAR) mechanisms. Standard imputation methods were applied before analysis. Method performance was influenced by missing data mechanism, with one exception for simple imputation. The greatest bias occurred under MNAR and large effect sizes. It is important to carefully investigate the missing data mechanism.     

Estimating a frequency distribution when the sampling is biased

A simple random sample on a random variable A allows its density to be consistently estimated, by a histogram or preferably a kernel density estimate. When the sampling is biased towards certain x-values these methods instead estimate a weighted version of the density function. This article proposes a method for estimating both the density and the sampling bias simultaneously. The technique requires two independent samples and utilises ideas from mark-recapture experiments. An estimator of the size of the sampled population also follows simply from this density estimate.     

Head over heels in debt?

The average household in the UK is in debt to the tune of nearly £9000—and that is not including the mortgage. Consumer borrowing, on credit cards, car and retail finance deals, overdrafts and unsecured personal loans was £4525 per average UK adult at the end of February 2007. Are we drowning in debt? Chris Tapp , Associate Director of Credit Action, reports.     

Seeing the woods — statistics for the very young

If you go down to the woods today … you're sure of a big statistical experience. You might run into Chris Du Feu giving 9-year-olds their first lesson in statistics. Tasks for the teacher? One, clear nettles; two, make sure that leaves will stay firmly stuck in place on the bar-chart…