Non-ignorable missing covariate data in survival analysis: a case-study of an International Breast Cancer Study Group trial

Summary.  Non-ignorable missing data, a serious problem in both clinical trials and observational studies, can lead to biased inferences. Quality-of-life measures have become increasingly popular in clinical trials. However, these measures are often incompletely observed, and investigators may suspect that missing quality-of-life data are likely to be non-ignorable. Although several recent references have addressed missing covariates in survival analysis, they all required the assumption that missingness is at random or that all covariates are discrete. We present a method for estimating the parameters in the Cox proportional hazards model when missing covariates may be non-ignorable and continuous or discrete. Our method is useful in reducing the bias and improving efficiency in the presence of missing data. The methodology clearly specifies assumptions about the missing data mechanism and, through sensitivity analysis, helps investigators to understand the potential effect of missing data on study results.     

“WHAT DOES SHE SEE IN HIM?”: THE EFFECT OF SHARING ON THE CHOICE OF SPOUSE

All husbands and wives share in the spoils of marriage. Sharing makes each partner a residual claimant and encourages spouses to provide marital inputs. However, because each spouse is only a partial residual claimant, each may be inclined to provide a "suboptimal" level of marital inputs. The choice of spouse influences the level of distortion, and under some circumstances the efficient mating is between individuals of equal value     

Statistics for weighing benefits and harms in a proposed genetic substudy of a randomized cancer prevention trial

Summary.  When evaluating potential interventions for cancer prevention, it is necessary to compare benefits and harms. With new study designs, new statistical approaches may be needed to facilitate this comparison. A case in point arose in a proposed genetic substudy of a randomized trial of tamoxifen versus placebo in asymptomatic women who were at high risk for breast cancer. Although the randomized trial showed that tamoxifen substantially reduced the risk of breast cancer, the harms from tamoxifen were serious and some were life threaten-ing. In hopes of finding a subset of women with inherited risk genes who derive greater bene-fits from tamoxifen, we proposed a nested case–control study to test some trial subjects for various genes and new statistical methods to extrapolate benefits and harms to the general population. An important design question is whether or not the study should target common low penetrance genes. Our calculations show that useful results are only likely with rare high penetrance genes.     

Real nonparametric regression using complex wavelets

Summary.  Wavelet shrinkage is an effective nonparametric regression technique, especially when the underlying curve has irregular features such as spikes or discontinuities. The basic idea is simple: take the discrete wavelet transform of data consisting of a signal corrupted by noise; shrink or remove the wavelet coefficients to remove the noise; then invert the discrete wavelet transform to form an estimate of the true underlying curve. Various researchers have proposed increasingly sophisticated methods of doing this by using real-valued wavelets. Complex-valued wavelets exist but are rarely used. We propose two new complex-valued wavelet shrinkage techniques: one based on multiwavelet style shrinkage and the other using Bayesian methods. Extensive simulations show that our methods almost always give significantly more accurate estimates than methods based on real-valued wavelets. Further, our multiwavelet style shrinkage method is both simpler and dramatically faster than its competitors. To understand the excellent performance of this method we present a new risk bound on its hard thresholded coefficients.     

Labor relations and technological change at Canadian Pacific Railway

There was a time in this fair land when the railroad did not run When the wild majestic mountains stood alone against the sun Long before the white man and long before the wheel When the green dark forest was too silent to be real For they looked into the future and what did they see They saw an iron road running from the sea to the sea Bringing the goods to a young growing land All up through the seaports and into their hands From “Canadian Railroad Trilogy” by Gordon Lightfoot The authors thank CPR managers and union officials representing CPR employees for their cooperation and patience in explaining the intricacies of the railroad industry. Special appreciation is extended to Jason Copping, Labour Relations Manager, for his facilitating our initial access to the company.     

In Whose Backyard?: Concern About Siting a Nuclear Waste Facility*

Proponents of hazardous and nuclear waste depositories label opponents to local siting of such facilities “NIMBYs” (Not In My Backyard). This study assesses the extent to which the NIMBY label and the strategies of industry proponents to reduce opposition function on a reasonable set of assumptions. Using survey data and multiple regression techniques, the levels of concern of residents living in the county selected as the site of a low level radioactive waste disposal facility (imminent threat condition) are compared with a statewide sample (hypothetical threat condition). Consistent with proponents' theoretical assumptions, the levels of concern are greater for respondents under conditions of imminent threat than of hypothetical threat. However, within the host county, levels of concern are lowest, albeit most polarized, in the community closest to the proposed site. A conflict theory approach enhances an understanding of these findings by suggesting that within the most proximate community levels of concern are lowest for citizens who stand to gain the most economic benefits from the facility but highest for those citizens who are least likely to derive tangible gains.