On the α-risks for shewhart control charts

The performance of the usual Shewhart control charts for monitoring process means and variation can be greatly affected by nonnormal data or subgroups that are correlated. Define the α_k-risk for a Shewhart chart to be the probability that at least one “out-of-control” subgroup occurs in k subgroups when the control limits are calculated from the k subgroups. Simulation results show that the α_k-risks can be quite large even for a process with normally distributed, independent subgroups. When the data are nonnormal, it is shown that the α_k-risk increases dramatically. A method is also developed for simulating an “in-control” process with correlated subgroups from an autoregressive model. Simulations with this model indicate marked changes in the α_k-risks for the Shewhart charts utilizing this type of correlated process data. Therefore, in practice a process should be investigated thoroughly regarding whether or not it is generating normal, independent data before out-of-control points on the control charts are interpreted to be due to some real assignable cause.     

Outcomes of a technology-based social norms intervention to deter alcohol use in freshman residence halls

OBJECTIVE: The authors tested a prototype intervention designed to deter alcohol use in residence halls. PARTICIPANTS: Approximately 384 freshmen participated in the study over a 2-year period. METHODS: The authors devised a feedback method that assessed residents' blood alcohol concentration (BAC) at night and allowed the readings to be retrieved the next day via the Web. Residents in an intervention hall received their BAC readings as well as normative feedback. In a comparison hall, residents could retrieve only the BAC readings. RESULTS: The authors found statistically significant hall differences, but they were small in size and not meaningful. CONCLUSIONS: Qualitative findings suggest the intervention had an overall positive impact, but the actions of a subgroup of rebellious drinkers might have obscured the effect. Social norms interventions could provoke some episodes of excessive drinking in students who find these messages objectionable. More research is needed to evaluate delayed BAC feedback.     

Drinking plans and drinking outcomes: examining young adults' weekend drinking behavior

This study examined relationships among drinking intentions, environments, and outcomes in a random sample of 566 undergraduate college students. Telephone interviews were conducted with respondents before and after a single weekend assessing drinking intentions for the coming weekend related to subsequent drinking behaviors. Latent class analyses found evidence for four distinct drinking environments distinguished by private/public setting and presence of few/many intoxicated people. There was evidence that the drinking environment mediated the relationship between drinking intentions and heavy episodic drinking in this young adult sample. Future research might focus on examining person/environment interactions as they relate to heavy episodic drinking.     

Effects of a social norm feedback campaign on the drinking norms and behavior of Division I student-athletes

Social norm feedback is a promising strategy for reducing alcohol misuse on college campuses. However, little is known about the impact of these interventions on at-risk populations, such as student-athletes. This study examined the effects of a campus-wide media campaign on Division I student-athletes at three universities. A discriminant function analysis revealed that a composite measure of perceived campus drinking norms distinguished between two campaign exposure groups. With the exception of one perceived norm measure (closest friends), the campaign-exposed group reported more conservative estimates of alcohol use in peers. However, there was no evidence that the campaign had reduced alcohol use. The inability of the campaign to reduce perceptions of alcohol use among one's closest friends may have accounted for the lack of change in drinking behavior. Discussion is directed to the potential limitations of using social norm feedback campaigns to reduce alcohol misuse in high-risk groups, such as student-athletes.     

A close look at why one social norms campaign did not reduce student drinking

The authors examined 3 possible explanations for the failure of a social norms campaign at a large public university. They administered an anonymous survey to 2 random samples of undergraduate classes: a baseline assessment of 616 students before the campaign's implementation and a follow-up survey of 723 students 4 academic years later. At follow-up, 66.5% of the students were aware of the campaign, yet the survey revealed no reduction in perceived drinking norms or alcohol use in this group. An analysis of the postcampaign sample revealed that (1) a majority of the students did not find the statistics used in the campaign messages credible, (2) higher levels of alcohol use predicted lower levels of perceived campaign credibility, and (3) only 38.5% of the students understood the campaign's intended purpose. If they are to influence personally relevant drinking norms, these campaigns must undergo further development to enhance message credibility and participants' understanding.     

Normative beliefs as risk factors for involvement in unhealthy weight control behavior

OBJECTIVE: The authors' aim in this study was to determine, after adjustment for the effects of body mass index and sociodemographic measures, whether sex-specific weight control norms would have significant independent relationships with the weight control behavior of college women and men. PARTICIPANTS: The authors used an anonymous questionnaire to assess a sample of 470 college students, aged 18 to 26 years, attending either a 2- year community college or a 4-year public university. METHODS: To calculate body mass index, the authors objectively measured the height and weight of each participant. They conducted separate discriminant function analyses for women and men. RESULTS: The discriminant function analyses clearly indicated that weight control norms of same-sex, close friends were the best discriminators of involvement in weight control. CONCLUSIONS: The findings indicate that perceived peer norms may be important but overlooked risk factors for engaging in unhealthy weight control practices. The authors discuss the implications of these findings in the context of student health promotion.     

Firm outsourcing decisions: evidence from U.S. foreign trade zones

This article examines the operations of firms located in U.S. foreign trade subzones to study the responsiveness of outsourcing to international cost changes. I find that firms reduce their reliance on foreign inputs when dollar depreciation increases the relative price of imported inputs. The effect is pervasive across industries and is economically significant. In addition, firms that rely more heavily on imported intermediate inputs reduce their overall shipments when dollar depreciation elevates their imported, input costs. However, the magnitude of the shipments effect is economically small, suggesting that firms respond to exchange rate movements by adjusting their operations on other dimensions.     

A test of the perceived norms model to explain drinking patterns among university student athletes

The author tested the ability of perceived drinking norms to discriminate among drinking patterns in a sample of National Collegiate Athletic Association (NCAA) Division I student athletes. He used an anonymous questionnaire to assess 297 athletes, representing 18 teams, at a public university in the Midwest. Alcohol use patterns showed considerable variation, with many athletes (37.1%) abstaining during their season of competition. A discriminant function analysis revealed that higher levels of alcohol involvement are disproportionately found among athletes who began drinking regularly at an early age. Perceived drinking norms were less important in the discrimination of student athlete drinker groups. Women and those with higher grade point averages were somewhat more likely to refrain from in-season drinking than other survey respondents.     

Elementary statistics laboratory

Students in elementary statistics traditionally see experiments and data as words and numbers in a text. They receive little exposure to the important statistical activities of sample selection, data collection, experimental design, development of statistical models, the need for randomization, selection of factors, etc. They often leave the first course without a firm understanding of the role of applied statistics or of the statistician in scientific investigations. In an attempt to improve elementary statistics education, we have developed a statistics laboratory similar to those of other elementary science courses. We will discuss our experiences in teaching a laboratory component with the traditional elementary statistics course. In each lab session, students, working in teams, discuss the design of an experiment, carry out the experiment, and analyze their data using Minitab on a Macintosh or MS-DOS based computer. The students then individually either answer a series of short answer questions or write a formal scientific report. The labs are designed to be relatively inexpensive and portable. They do not require a prior background in science, statistics or computing.     

Smooth nonparametric quantile estimation under censoring: simulations and bootstrap methods

Based on right-censored data from a lifetime distribution F , a smooth nonparametric estimator of the quantile function Q (p) is given by Qn(p)=h 1jjQn(t)K((t-p)/h)dt, where QR(p) denotes the product-limit quantile function. Extensive Monte Carlo simulations indicate that at fixed p this kernel-type quantile estimator has smaller mean squared error than (L(p) for a range of values of the bandwidth h. A method of selecting an "optimal" bandwidth (in the sense of small estimated mean squared error) based on the bootstrap is investigated yielding results consistent with the simulation study. The bootstrap is also used to obtain interval estimates for Q (p) after determining the optimal value of h.