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.     

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.     

Measuring Substance Abuse Treatment Need Among Adults in Florida: A Social Indicators Approach

Determining the size and demographiccharacteristics of substance abuse populationsis extremely important for implementing publicpolicies aimed at the control of substanceabuse. Such information not only assists in theallocation of limited treatment resources bythe state, but also in the monitoring ofsubstance abuse trends over time and in theevaluation of innovative policy initiatives. Inthis study, we develop three composite measuresof treatment need. We then use these measuresto estimate treatment need for alcohol abuseand for controlled substance abuse within eachof Florida's 67 counties. This study providesan important empirical component of communityplanning, quantifying and, to a limited degree,specifying the level of need for the substanceabuse treatment of community residents. Anadditional benefit is the development of a costeffective and unobtrusive methodology fordetermining empirically when levels of need arechanging so that treatment levels can beadjusted accordingly. With proper use,policymakers can readily employ the methodologydeveloped in this study in Florida andelsewhere to make better-informed decisions inthe allocation of finite substance abusetreatment resources.     

Implications of temporal aggregation on the relation between two time series

Using a simple theoretical model and giving an empirical example it is investigated if it matters whether we use (monthly) averages or end-of-period (month) data in performing Granger-causality tests. It is shown that no major problems are to be expected if the two series are temporally aggregated in the same way, but non-trivial problems can occur if the two series have different kinds of temporal aggregation.     

Rural Income-Generating Programs and Fertility Limitation: Evidence from a Microdemographic Study in Nepal1

Abstract Participation in rural development programs that organize members into local cooperative groups can alter the decision-making environment facing couples to reflect some of the negative consequences of childbearing. This study uses data from Nepal, collected through a combination of ethnographic and survey methods, to test the effects of participation in such a development program on fertility behavior. Results demonstrate that program participants are much more likely to use contraceptives to limit their fertility than are non-participants. The study provides empirical support for theories linking this type of institutional change to fertility and indicates a policy option that can allow some negative consequences of childbearing to affect couples' fertility decisions.     

A SCALE IN SEARCH OF A CONSTRUCT: COMMENTS ON GAVIN AND WAMBOLDT

The article examines some issues raised in Gavin and Wamboldt's (1992) recent study on the Family-of-Origin Scale (FOS) (Hovestadt, Anderson, Piercy, Cochran, & Fine, 1985). The discussion centers on unresolved concerns regarding the validity and utility of the FOS and on unsubstantiated and potentially misleading claims made in the Gavin and Wamboldt article. A case is made for conceptual and methodological precision in the study of family phenomena.     

Multicultural perspectives on counseling survivors of rape

The dominant Euro-American culture is a rape-prone culture, as defined by Sanday. Within that culture, rape is both a tool and a consequence of interlocking systems of oppression based on race, ethnicity, class, and sexual orientation. The impact of rape on an individual survivor can only be fully understood in the context of the survivor's own culture, religious beliefs, and experience as an immigrant or refugee. Issues of race, culture, class, and sexual orientation influence every step in the counseling of a rape survivor. Knowledge about the client's culture is essential if accurate assessment and culturally appropriate service are to be provided. Specific examples of the impact of these issues are presented. Ways in which the cultural values implicit in the crisis counseling model may conflict with the client's values and needs are examined.     

Robust confidence interval for a residual standard deviation

The residual standard deviation of a general linear model provides information about predictive accuracy that is not revealed by the multiple correlation or regression coefficients. The classic confidence interval for a residual standard deviation is hypersensitive to minor violations of the normality assumption and its robustness does not improve with increasing sample size. An approximate confidence interval for the residual standard deviation is proposed and shown to be robust to moderate violations of the normality assumption with robustness to extreme non-normality that improves with increasing sample size.