A note on inverse estimation in non-linear models

The problem of estimating the value of an x variable for a given proportion of an observed value of the y variable is consdered for a non-linear model. Asymptotic confidence limits are obtained and an application of the method is illustrated witreal data.     

DRUG POLICY IN THE TIME OF AIDS:

In 1985, the National Institute on Drug Abuse (NIDA) funded an ethnographic research project in San Francisco to study the needle sharing behavior of injection drug users (IDUs). The goal of the research was to develop a strategy to slow the spread of HIV among this hidden and hard to reach population of drug users and their sexual partners. This small-scale project grew into a model intervention in which bleach, condoms, and street-based education by outreach workers were employed to inform IDUs of the risk of AIDS and of methods for protecting themselves. The "reach and teach bleach" model was adopted by NIDA and implemented in a number of American cities. This study describes the development of the model intervention, the adoption of the model by NIDA as part of its National AIDS Demonstration Research (NADR) project, and the political circumstances under which the city of San Francisco applied for the NADR grant. Drawing on Social Worlds/Arena theory, and based on extensive interviews and participant observation, a sociohistorical analysis examines the initial development, implementation, and disintegration of the model outreach project and the impact of the program on drug policy in the city of San Francisco.     

Naturally occurring play patterns in groups of latency aged children

This study examines the influence of the socialization of aggression among different gender and social class groupings and the influence of psychosocial stage on cognitive developmental play preferences among groups of school aged children. Observations of 143 play groups were coded for play preference (symbolic play, practice play, games with rules) and play performance (cooperative or competitive). Findings of the log-linear data analysis suggest a middle class and masculine bias in Piaget's cognitive model (i.e., that as age increases children prefer more games with rules). This model held only for middle class and affluent boys. Girls (both latency and prepubertal) and lower socioeconomic groups tended to prefer practice play. Girls were more likely to play cooperatively; boys more likely to play competitively. Implications for theory development and clinical practice are explored.     

The Impact of Items and Anchors on Parent–Child Reports of Problem Behavior

Research has repeatedly demonstrated that parent and child reports of child behavior and emotional functioning often do not agree in terms of symptom severity or even symptom presence. Given the potential clinical impact that discrepant reports may have on the therapeutic process, a significant amount of research has addressed the factors influencing this observed discrepancy. Traditionally, this research has evaluated the impact of demographic factors on mean differences and obtained correlation coefficients between parent and child reports. The current research improves upon previous research in this area in two ways. First, the current research uses parent and child measures with identical rather than similar items as is commonly found in previous research. Second, the current research moves beyond identifying demographic influences on discrepant reports by explaining observed discrepancies in terms of differences in parent and child perceptions of typical child behavior.David Carlston and Benjamin Ogles are affiliated with Department of Psychology, Ohio University, Athens, USA.Funding for this project was provided by the Ohio Department of Mental Health.     

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.     

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.