Type I error rates from likelihood‐based repeated measures analyses of incomplete longitudinal data

The last observation carried forward (LOCF) approach is commonly utilized to handle missing values in the primary analysis of clinical trials. However, recent evidence suggests that likelihood‐based analyses developed under the missing at random (MAR) framework are sensible alternatives. The objective of this study was to assess the Type I error rates from a likelihood‐based MAR approach – mixed‐model repeated measures (MMRM) – compared with LOCF when estimating treatment contrasts for mean change from baseline to endpoint (Δ). Data emulating neuropsychiatric clinical trials were simulated in a 4 × 4 factorial arrangement of scenarios, using four patterns of mean changes over time and four strategies for deleting data to generate subject dropout via an MAR mechanism. In data with no dropout, estimates of Δ and SE_Δ from MMRM and LOCF were identical. In data with dropout, the Type I error rates (averaged across all scenarios) for MMRM and LOCF were 5.49% and 16.76%, respectively. In 11 of the 16 scenarios, the Type I error rate from MMRM was at least 1.00% closer to the expected rate of 5.00% than the corresponding rate from LOCF. In no scenario did LOCF yield a Type I error rate that was at least 1.00% closer to the expected rate than the corresponding rate from MMRM. The average estimate of SE_Δ from MMRM was greater in data with dropout than in complete data, whereas the average estimate of SE_Δ from LOCF was smaller in data with dropout than in complete data, suggesting that standard errors from MMRM better reflected the uncertainty in the data. The results from this investigation support those from previous studies, which found that MMRM provided reasonable control of Type I error even in the presence of MNAR missingness. No universally best approach to analysis of longitudinal data exists. However, likelihood‐based MAR approaches have been shown to perform well in a variety of situations and are a sensible alternative to the LOCF approach. MNAR methods can be used within a sensitivity analysis framework to test the potential presence and impact of MNAR data, thereby assessing robustness of results from an MAR method. Copyright © 2004 John Wiley & Sons, Ltd.     

Implied Preference for Seismic Design Level and Earthquake Insurance

Seismic risk can be reduced by implementing newly developed seismic provisions in design codes. Furthermore, financial protection or enhanced utility and happiness for stakeholders could be gained through the purchase of earthquake insurance. If this is not so, there would be no market for such insurance. However, perceived benefit associated with insurance is not universally shared by stakeholders partly due to their diverse risk attitudes. This study investigates the implied seismic design preference with insurance options for decisionmakers of bounded rationality whose preferences could be adequately represented by the cumulative prospect theory (CPT). The investigation is focused on assessing the sensitivity of the implied seismic design preference with insurance options to model parameters of the CPT and to fair and unfair insurance arrangements. Numerical results suggest that human cognitive limitation and risk perception can affect the implied seismic design preference by the CPT significantly. The mandatory purchase of fair insurance will lead the implied seismic design preference to the optimum design level that is dictated by the minimum expected lifecycle cost rule. Unfair insurance decreases the expected gain as well as its associated variability, which is preferred by risk-averse decisionmakers. The obtained results of the implied preference for the combination of the seismic design level and insurance option suggest that property owners, financial institutions, and municipalities can take advantage of affordable insurance to establish successful seismic risk management strategies.     

Bayesian analysis of discrete time warranty data

Summary.  The analysis of warranty claim data, and their use for prediction, has been a topic of active research in recent years. Field data comprising numbers of units returned under guarantee are examined, covering both situations in which the ages of the failed units are known and in which they are not. The latter case poses particular computational problems for likelihood-based methods because of the large number of feasible failure patterns that must be included as contributions to the likelihood function. For prediction of future warranty exposure, which is of central concern to the manufacturer, the Bayesian approach is adopted. For this, Markov chain Monte Carlo methodology is developed.     

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.     

Estimation of Hazard, Density and Survivor Functions for Randomly Censored Data

Maximum likelihood estimation and goodness-of-fit techniques are used within a competing risks framework to obtain maximum likelihood estimates of hazard, density, and survivor functions for randomly right-censored variables. Goodness-of- fit techniques are used to fit distributions to the crude lifetimes, which are used to obtain an estimate of the hazard function, which, in turn, is used to construct the survivor and density functions of the net lifetime of the variable of interest. If only one of the crude lifetimes can be adequately characterized by a parametric model, then semi-parametric estimates may be obtained using a maximum likelihood estimate of one crude lifetime and the empirical distribution function of the other. Simulation studies show that the survivor function estimates from crude lifetimes compare favourably with those given by the product-limit estimator when crude lifetimes are chosen correctly. Other advantages are discussed.     

Time, Self, and the Curiously Abstract Concept of Agency*

The term "agency" is quite slippery and is used differently depending on the epistemological roots and goals of scholars who employ it. Distressingly, the sociological literature on the concept rarely addresses relevant social psychological research. We take a social behaviorist approach to agency by suggesting that individual temporal orientations are underutilized in conceptualizing this core sociological concept. Different temporal foci—the actor's engaged response to situational circumstances—implicate different forms of agency. This article offers a theoretical model involving four analytical types of agency ("existential,""identity,""pragmatic," and "life course") that are often conflated across treatments of the topic. Each mode of agency overlaps with established social psychological literatures, most notably about the self, enabling scholars to anchor overly abstract treatments of agency within established research literatures.     

Gender and the 'New Paradigm' of Health

This article provides a critical review of literature on the relationship between gender and the 'new paradigm' of health. An overview of the feminist critique of health is given, from the Women's Health Movement of the late 1960s and early feminist debates about medicalisation, to more recent discussions about structural inequalities between men and women, eating disorders, and AIDS. I then go on to explore the feminist response to the so-called 'new paradigm' of health (an approach that emphasises health promotion, individual responsibility for health, and body-monitoring). Arguments that health promotion initiatives target women and confirm their position as principal guardians of health within the family are considered, as well as literature on the breast cancer awareness campaign. I then explore the growing body of literature on masculinity and health, and its account of the relationship between gender and current ideas about healthiness. Finally, I offer up some suggestions for the direction a new feminist critique of health might take.     

Neither ‘family’ nor ‘corporate’ farming: Australian tomato growers as farm family entrepreneurs

For the past two decades there has been much debate about the future of family farming. The basic question on which this debate has turned is whether current pressures on family farm systems should be understood as symptomatic of a terminal condition, in which farmers are replaced progressively by corporate ownership; or whether family farms will persist as a social formation, albeit increasingly subsumed by off-farm interests. Using evidence from the Australian processing tomato sector, this article documents the changing social and economic formation of ‘family farming’. We argue that in this industry, the appropriate way to describe farmers is through the deployment of that a new category of farming; farm family entrepreneurs. This phrase is coined to describe the situation where family units remain at the social and economic heart of farm ownership and operation, but in the context where they relate to their land-based assets through legal and financial structures characteristic of the wider economy. As this article explores, this formation seems to represent an accommodating modus operandi for farm units within neo-liberal agricultural governance. Nevertheless, however, this duality of family-based structures and capitalist entrepreneurialism inevitably provokes a series of tensions, whose resolution requires a variety of organizational strategies to be put in place.     

From critical sociology to public intellectual: Pierre Bourdieu and politics

By the late 1990s, Pierre Bourdieu had become the primary public intellectual of major social scientific status at the head of the anti-globalization movement that emerged in France and in other Western European countries. This article discusses how Bourdieu became a leading public intellectual, a role that seems to contrast with his early years as a professional sociologist. It explores what seemed to change in Bourdieu’s activities and outlook as sociologist and what seems to have remained constant. It identifies several institutional conditions that seemed necessary for Bourdieu to be able to play the kind of public intellectual role he did in his later years. Bourdieu’s movement from a peripheral position to a central location in the French intellectual field, the changing character of the field itself, the growing influence of the mass media in French political and cultural life, the failures of the French Socialists in power, a cultural legacy of leading critical intellectuals in France, a unifying national issue of globalization, and the political conjuncture in 1995 all intersected in ways that opened a path for Bourdieu to choose new and more frequent forms of political action. His responses to that combination of factors at different moments reveal both a striking continuity in desire to preserve the autonomy of intellectual life and a change in view and strategy on how best to do that. The article concludes with a brief evaluation of Bourdieu’s public intellectual role.