Tests of the causal directions of global — Life facet satisfaction relationships

Previous research generally has supported multiple discrepancies theory (MDT) of the processes by which individuals arrive at judgments of satisfaction with various aspects of their lives as well as with life overall. However, the nature of possible causal relationships between overall and life facet satisfaction has been ignored. The purpose of this study was to extend MDT by testing alternative theoretical models which specified Bottom-up, Top-Down, and Bidirectional relationships between overall life satisfaction and satisfaction with 11 life facets in a sample of 1354 U.S. college students. Results most strongly favored the Bidirectional model in which the overall — life facet satisfaction relationship varied across life domains. The need to identify boundary conditions which determine the direction of the overall — life facet satisfaction relationship is discussed.     

Measuring the affective quality of life of university students: The validation of an instrument

The purpose of this study is to develop an instrument for measuring the quality of life of university students, and to report its validity and reliability. The study used a representative sample of undergraduate and graduate students in the faculty of education at a major Canadian university. The construct validity of the scales was assessed by Piazza's technique for the analysis of attitude items. The findings supported conceptualizing the quality of life of university students in four dimensions including Positive Affect, Interaction with Students, Interaction with Professors, and Negative Affect. The alpha reliabilities of these scales ranged from 0.75 to 0.93. Some potential applications of this instrument for understanding educational attainment, as well as for the evaluation of university departments and faculties, are mentioned.     

Life events and peer substance use and their relation to substance use problems in college students

Substance use disorders among college students are not well understood, and the present study examined the relationship of two environmental factors to alcohol and drug use problems in 616 (316 women) college students. Participants completed measures assessing substance use problems, life events, and substance use among peers. Alcohol use problems were significantly associated with higher drug use problems and regular use of illicit drugs among friends. Drug use problems were significantly associated with male gender, higher alcohol use problems, regular use of alcohol and drugs among friends, illicit drug use among romantic partners, and higher numbers of negative life events. Results extend previous research and suggest that college students who experience multiple negative life events and/or affiliate with substance using friends and romantic partners may be at risk for developing a substance use problem.     

Differences between actual and perceived student norms: an examination of alcohol use, drug use, and sexual behavior

Researchers in the social norms area have previously focused primarily on alcohol consumption, paying comparatively less attention to drug use and sexual behavior. The major purposes of this study were to (1) compare perceptions of peer norms in the areas of alcohol use, drug use, and sexual behavior with actual behavior and (2) determine if a relationship existed between a student's perceptions of normative behavior and a student's actual behavior. Participants were 833 college students at a large, public university in the Northeast. Study participants overestimated alcohol use, drug use, and sexual behavior among their peers. There was also a positive relationship between actual behavior and perceived peer norms, although the effect sizes for all behaviors were small to moderate. The authors provide further support for the tenets of social norms theory and suggest that social norms interventions are appropriate both campus-wide and to targeted high-risk groups.     

Community exercise program for older adults recovering from hip fracture: a pilot study

Community-based rehabilitative exercise programs might be an effective means to improve functional outcomes for hip-fracture patients. The purpose of this study was to evaluate the effectiveness of a community exercise program (CEP) for older adults recovering from hip fracture. Twenty-five older adults (mean age 80.0 +/- 6.0 years; 24 women; 71 +/- 23 days post-hip fracture) participated in this pilot study (17 exercise, 8 control). The CEP involved functional stepping and lower extremity-strengthening exercises. Control participants received only standard outpatient therapy. Measures of functional mobility, balance confidence, falls efficacy, lower extremity strength, and daily physical activity were evaluated at baseline and at 16 weeks. Improvements for self-reported physical activity, mobility, balance, and knee-extensor strength were observed for the CEP group. This study demonstrated that a CEP is beneficial for community-dwelling older adults post-hip fracture.     

Endurance exercise and leg strength in older women

Quadriceps strength and mass peak in the third decade of life, plateau, and then decline from the fifth decade on. To examine the influence of chronic endurance training and age on lean mass and leg strength, women runners (n = 62, age 43-69 years) and sedentary participants (n = 33, age 43-66 years) were divided into 40-, 50-, and 60-year age groups. Absolute isokinetic concentric torque did not differ between runners and sedentary women (97.9 +/- 19.5 and 104.6 +/- 22.7 N . m, respectively, p = .18) but was different between age groups independent of exercise status (107.6 +/- 18.4, 97.1 +/- 19.9, and 90.1 +/- 21.4 N . m, for 40s, 50s, and 60s, respectively, p < .05). Lean body mass also differed by age group (p < .05) but did not change differently among runners and sedentary women. These findings suggest that chronic endurance training might not influence the loss of muscle mass and muscle strength that occur with aging.     

A Bootstrap Stationarity Test for Predictive Regression Invalidity

In order for predictive regression tests to deliver asymptotically valid inference, account has to be taken of the degree of persistence of the predictors under test. There is also a maintained assumption that any predictability in the variable of interest is purely attributable to the predictors under test. Violation of this assumption by the omission of relevant persistent predictors renders the predictive regression invalid, and potentially also spurious, as both the finite sample and asymptotic size of the predictability tests can be significantly inflated. In response, we propose a predictive regression invalidity test based on a stationarity testing approach. To allow for an unknown degree of persistence in the putative predictors, and for heteroscedasticity in the data, we implement our proposed test using a fixed regressor wild bootstrap procedure. We demonstrate the asymptotic validity of the proposed bootstrap test by proving that the limit distribution of the bootstrap statistic, conditional on the data, is the same as the limit null distribution of the statistic computed on the original data, conditional on the predictor. This corrects a long-standing error in the bootstrap literature whereby it is incorrectly argued that for strongly persistent regressors and test statistics akin to ours the validity of the fixed regressor bootstrap obtains through equivalence to an unconditional limit distribution. Our bootstrap results are therefore of interest in their own right and are likely to have applications beyond the present context. An illustration is given by reexamining the results relating to U.S. stock returns data in Campbell and Yogo (2006 Campbell, J. Y. and Yogo, M. (2006), “Efficient Tests of Stock Return Predictability,” Journal of Financial Economics, 81, 27–60.[Crossref], [Web of Science ®] , [Google Scholar]). Supplementary materials for this article are available online.     

Inferactive data analysis

We describe inferactive data analysis, so-named to denote an interactive approach to data analysis with an emphasis on inference after data analysis. Our approach is a compromise between Tukey's exploratory and confirmatory data analysis allowing also for Bayesian data analysis. We see this as a useful step in concrete providing tools (with statistical guarantees) for current data scientists. The basis of inference we use is (a conditional approach to) selective inference, in particular its randomized form. The relevant reference distributions are constructed from what we call a DAG-DAG—a Data Analysis Generative DAG, and a selective change of variables formula is crucial to any practical implementation of inferactive data analysis via sampling these distributions. We discuss a canonical example of an incomplete cross-validation test statistic to discriminate between black box models, and a real HIV dataset example to illustrate inference after making multiple queries on data.     

KIDS OR CASH? EXPLORING CHARTER SCHOOL RESPONSES TO DECLINING GOVERNMENT REVENUES

While the literature is extensive on school districts' revenue sources, less research has been done on the impact of donations on school district funds. In this paper, we extend the theoretical literature on crowding out of private donations by government grants for one type of nonprofit firm, namely charter schools. The theoretical model leads us to focus on the key relationships among fundraising effort, enrollment (which is tied to federal and state funding) and donations. Using a dataset on Texas charter schools we adopt a two-stage approach to examine the empirical relationship between changes in nondonor revenues and the donations received by charter schools. Like the extensive empirical estimates of the effects of government grants on donations for other types of nonprofit firms, we find evidence of crowding-out with respect to our sample of charter schools. We also find a significant, positive effect of fundraising on donations with a $1 increase in fundraising associated to a $0.58 increase in donations, a pattern consistent with overinvestment in fundraising. Enrollments exhibit a robust inverse relationship to changes in nondonor revenues. (JEL H00, H32, H50)