MANAGING ACADEMIC INTERDISCIPLINARY RESEARCH PROJECTS*

This field study provides variables that can be used by practitioners as action levers and by future researchers as the basis for theoretical development. Conclusions from relevant literature and findings from interviews with interdisciplinary research management identified forty variables that were viewed as important to interdisciplinary research project success. After adjusting the data for reliability attenuation, these variables were further analyzed to identify the best prediction equation. The findings suggested that project age or the longevity of the project and open discussion of disagreements were the best predictors of performance.     

An Experimental Test of the Effects of Fictional Framing on Attitudes*

Objectives. Most studies of media effects in political communication focus on news media. A smaller body of work extends theories of news media effects to fictional entertainment media. Just as news media engage in priming and agenda setting, these studies suggest that fictional media do as well. In this study, we deal with fictional media's framing of issues. No research has sought to test the effects of framing in explicitly fictional media on political opinions. We develop the outlines of a theory we call “fictional framing” and test it in an experiment. Methods. Participants in our treatment group watched the film Cider House Rules. The movie frames the issue of abortion in the case of incest in a pro‐choice way, and frames morality in terms of following one's own conscience. Results. The film influenced opinions in ways consistent with the framing of these issues. Conclusions. Since abortion opinions and moral values tend to be entrenched, we consider this a strong first test of the effects of fictional framing.     

Religious affiliation and Hispanic health in Utah

Two research hypotheses are addressed in this study. (1) Do health trajectories of Hispanics in Utah differ from what has been documented in states with longstanding large Hispanic populations? (2) Do non-Mormon groups in Utah have less favorable health status than Mormons in Utah? This study employs three health outcome measures: activity limitations caused by emotional problems, activity limitations caused by physical problems, and self-rated health status using the 2001 Utah Health Status Survey. Comparisons of Hispanics in their traditional settings within the U.S. generally show more favorable health status for Hispanics than for whites. We find little difference in health status between Hispanics in Utah and their Anglo counterparts. Hispanics were more likely than Anglos to have “a little” activity limitation due to physical problems, but were not more likely to report “a little” or “considerable” activity limitations due to emotional or physical problems. Hispanics and Anglos were statistically equal in probability of self-reported fair to poor health. Important in relation to studies outside of Utah, we find little support for the epidemiologic paradox, the usual finding of more favorable health for Hispanics than for whites. As with ethnicity, we find little difference between non-Mormon and Mormons with respect to health. The most notable exception is that Mormon Hispanics are at a significantly greater risk of emotional problems than Catholic Hispanics in Utah.     

A vector of quarters representation for bivariate time series

In this paper it is shown that several models for a bivariate nonstationary quarterly time series are nested in a vector autoregression with cointegration restrictions for the eight annual series of quarterly observations. Or, the Granger Representation Theorem is extended to incorporate, e.g., seasonal and periodic cointegration.     

Testing Variability in the Two-Sample Case

A number of robust methods for testing variability have been reported in previous literature. An examination of these procedures for a wide variety of populations confirms their general robustness. Shoemaker's improvement of the F test extends that test use to a realistic variety of population shapes. However, a combination of the Brown–Forsythe and O'Brien methods based on testing kurtosis is shown to be conservative for a wide range of sample sizes and population distributions. The composite test is also shown to be more powerful in most conditions than other conservative procedures.     

Orthogonally Blocked Mixture Experiments in Ellipsoidal Restricted Regions

In practical situations involving mixtures formed from several ingredients, interest is sometimes centered on the response in an ellipsoidal neighborhood around a standard formulation. We show that standard, orthogonally blocked, response surface designs, defined on a q ? 1 dimensional unit sphere, may be transformed into similarly orthogonally blocked q-ingredient mixture designs defined within an ellipsoid centered at the standard formulation. The method is illustrated using several examples of mixture experiments with three, four, and five ingredients, arranged in two, three, or four orthogonal blocks, obtained by projecting standard central composite designs and Box–Behnken designs into the ellipsoidal mixture region. Rotations of the resulting designs within the ellipsoidal regions are also considered.     

The best subset of parameters in min-max linear regression

These Fortran-77 subroutines provide building blocks for Generalized Cross-Validation (GCV) (Craven and Wahba, 1979) calculations in data analysis and data smoothing including ridge regression (Golub, Heath, and Wahba, 1979), thin plate smoothing splines (Wahba and Wendelberger, 1980), deconvolution (Wahba, 1982d), smoothing of generalized linear models (O'sullivan, Yandell and Raynor 1986, Green 1984 and Green and Yandell 1985), and ill-posed problems (Nychka et al., 1984, O'sullivan and Wahba, 1985). We present some of the types of problems for which GCV is a useful method of choosing a smoothing or regularization parameter and we describe the structure of the subroutines.Ridge Regression: A familiar example of a smoothing parameter is the ridge parameter X in the ridge regression problem which we write.     

Robust estimation methods for exponential data: a monte-carlo comparison

We compare the performance of seven robust estimators for the parameter of an exponential distribution. These include the debiased median and two optimally-weighted one-sided trimmed means. We also introduce four new estimators: the Transform, Bayes, Scaled and Bicube estimators. We make the Monte Carlo comparisons for three sample sizes and six situations. We evaluate the comparisons in terms of a new performance measure, Mean Absolute Differential Error (MADE), and a premium/protection interpretation of MADE. We organize the comparisons to enhance statistical power by making maximal use of common random deviates. The Transform estimator provides the best performance as judged by MADE. The singly-trimmed mean and Transform method define the efficient frontier of premium/protection.