Causal inference with generalized structural mean models

Summary.  We estimate cause–effect relationships in empirical research where exposures are not completely controlled, as in observational studies or with patient non-compliance and self-selected treatment switches in randomized clinical trials. Additive and multiplicative structural mean models have proved useful for this but suffer from the classical limitations of linear and log-linear models when accommodating binary data. We propose the generalized structural mean model to overcome these limitations. This is a semiparametric two-stage model which extends the structural mean model to handle non-linear average exposure effects. The first-stage structural model describes the causal effect of received exposure by contrasting the means of observed and potential exposure-free outcomes in exposed subsets of the population. For identification of the structural parameters, a second stage 'nuisance' model is introduced. This takes the form of a classical association model for expected outcomes given observed exposure. Under the model, we derive estimating equations which yield consistent, asymptotically normal and efficient estimators of the structural effects. We examine their robustness to model misspecification and construct robust estimators in the absence of any exposure effect. The double-logistic structural mean model is developed in more detail to estimate the effect of observed exposure on the success of treatment in a randomized controlled blood pressure reduction trial with self-selected non-compliance.     

How Welfare Policies Affect Adolescents' School Outcomes: A Synthesis of Evidence From Experimental Studies

Using data from 8 random assignment studies and employing meta‐analytic techniques, this article provides systematic evidence that welfare and work policies targeted at low‐income parents have small adverse effects on some school outcomes among adolescents ages 12 to 18 years at follow‐up. These adverse effects were observed mostly for school performance outcomes and occurred in programs that required mothers to work or participate in employment‐related activities and those that encouraged mothers to work voluntarily. The most pronounced negative effects on school outcomes occurred for the group of adolescents who had a younger sibling, possibly because of the increased home and sibling care responsibilities they assumed as their mothers increased their employment.     

Foster parenting: A developmental model

This paper proposes a developmental framework for foster parents and outlines four distinct growth stages. Such a framework can be of value to program administrators who are required to assess foster parent development during the crucial matching process. To draw a distinction between each developmental stage, specific instrumental tasks and indicators are outlined.     

Psychological Control and Autonomy Granting: Opposite Ends of a Continuum or Distinct Constructs?

This article explores the relationship between parental psychological control and parental autonomy granting, and the relations between these constructs and indicators of adolescent psychosocial functioning, in a sample of 9,564 adolescents from grades 9 to 12. Participants completed a comprehensive parenting questionnaire as well as several measures of psychosocial adjustment. Confirmatory factor analyses of the parenting items revealed discrete factors for psychological control and autonomy granting, suggesting that these are distinct parenting constructs rather than opposite ends of a parental control continuum. Moreover, structural equation modeling showed that these factors were weakly correlated and differentially related to adolescent internalizing symptoms. Findings have implications for future conceptualization and measurement of psychological control and autonomy granting, and for research examining their effects on adolescent development.     

Improving the contributions of technology assessment to the health care system of the U.S.A.

Summary Based on 14 case studies of highly effective therapies and the reasons they succeeded less frequently than they could, we propose a variety of steps to improve the health care system of the U.S.A. Whatever proposal emerges from current national debates until innovations are shown to be safe and effective, they should not be supported; when slightly better technologies are much more expensive than other good ones we need to consider appropriate choices carefully; simplified billing and bookkeping would reduce our costs; when a technology is rapidly introduced cautionnary measures may be needed; tracking immunization and repairing their omissions requires a new system; educational programs such as seen effective in hypertension should be applied in other areas such as vaccination; in organ transplantation the nation should consider “presumed consent”; our payment system sometimes creates perverse incentives and therefore needs review; and the preferences of the public in allocation of health resources need to be discovered once the public is informed about the issues. Research supported by Andrew W. Mellon Foundation.     

The analysis of incomplete data using stochastic covariates

In the development of many diseases there are often associated random variables which continuously reflect the progress of a subject towards the final expression of the disease (failure). At any given time these processes, which we call stochastic covariates, may provide information about the current hazard and the remaining time to failure. Likewise, in situations when the specific times of key prior events are not known, such as the time of onset of an occult tumour or the time of infection with HIV-1, it may be possible to identify a stochastic covariate which reveals, indirectly, when the event of interest occurred. The analysis of carcinogenicity trials which involve occult tumours is usually based on the time of death or sacrifice and an indicator of tumour presence for each animal in the experiment. However, the size of an occult tumour observed at the endpoint represents data concerning tumour development which may convey additional information concerning both the tumour incidence rate and the rate of death to which tumour-bearing animals are subject. We develop a stochastic model for tumour growth and suggest different ways in which the effect of this growth on the hazard of failure might be modelled. Using a combined model for tumour growth and additive competing risks of death, we show that if this tumour size information is used, assumptions concerning tumour lethality, the context of observation or multiple sacrifice times are no longer necessary in order to estimate the tumour incidence rate. Parametric estimation based on the method of maximum likelihood is outlined and is applied to simulated data from the combined model. The results of this limited study confirm that use of the stochastic covariate tumour size results in more precise estimation of the incidence rate for occult tumours.     

Gender-specific changes in students' sexual behaviors and attitudes at a southeastern university between 1973 and 1988.

This study investigated the gender-specific, self-reported sexual behaviors and attitudes of never-married college students attending a southeastern university in 1973 and 1988. Data were collected by means of a mailed questionnaire that remained essentially unchanged for both years. The authors found that both men and women reported an increase in heterosexual relationships that included sexual intercourse and a decrease in nonsexual relationships with the other gender. The majority of the students perceived themselves as adequately informed about sexuality and satisfied with their relationships, although the proportion of men who reported being satisfied with their relationships declined over the 15 years. The students indicated that sexuality education should focus primarily on information about AIDS and on preparation for marriage.     

Testing for state and local government job queues

Bivariate probit estimates with partial observability identify the factors influencing the worker’s decision to seek a state or local government job and the factors influencing the government’s decision to hire particular workers. The estimates routinely confirm the presence of a local job queue but confirm the presence of a state job queue only when the role of unionization is explicitly recognized. Our results suggest that the net benefits from local and state government employment are greater than those from private sector employment. The estimates also indicate that local governments disproportionately hire racial minorities relative to the local governments’ pool of applicants but indicate no such relationship for state governments. The authors thank Dale Belman, Jugal Ghorai, and Matt Higgins for help on this and related work. We also thank the referee and the editor for useful suggestions.