Robert A. Muenchen

Quantitative analysis of EEG in boys with attention-deficit-hyperactivity disorder: Controlled study with clinical implications

Sixteen-channel topographic brain mapping of electroencephalograms of 25 right-handed males, 9-12 years of age, with attention-deficit-hyperactivity disorder revealed increased theta (4-7.75 Hz) and decreased beta 1 (12.75-21 Hz) when compared with 27 controls matched for age and grade level. The differences were greater when patients were tested for reading and drawing skills, but were decreased when they were at rest during visual fixation. Although the differences in patients with attention-deficit-hyperactivity disorder were generalized, increased theta was more prominent in frontal regions, while beta 1 was significantly decreased in temporal regions. Principal component analysis was used to combine the variables into 2 components which accounted for 82% of the total variance. A discriminant function analysis using these components was able to predict group membership for attention-deficit-hyperactivity disorder patients 80% of the time and 74% for controls. These findings support the use of topographic electroencephalography for further elucidation of the neurophysiology of attention-deficit-hyperactivity disorder.

Help and Documentation

The full Stata package comes with 17 volumes of reference manuals. Both these manuals and the Stata help files are well written and authoritative and their style is consistent. They are of great help to beginners through advanced users.

Methylphenidate Effects on EEG, Behavior, and Performance in Boys With ADHD

The psychophysiologic and behavioral effects of methylphenidate were assessed in boys with attention deficit hyperactivity disorder between the ages of 9 and 11 years. The effects of methylphenidate on the EEG during baseline and cognitive tasks were evaluated using spectral analysis. Both subjective (rating scales) and objective (continuous performance) measures were administered and analyzed in conjunction with the electrophysiologic data. Although methylphenidate induced regional changes in the EEG under certain task-specific conditions, it had no global effects. Behavioral and performance measures improved with methylphenidate.

A novel thrombelastograph® tissue factor/kaolin assay of activated clotting times for monitoring heparin anticoagulation during cardiopulmonary bypass

We used a thrombelastograph (TEG®) assay with tissue factor and kaolin (TEG® TF/K) to measure activated clotting time (ACT) in 31 patients during cardiopulmonary bypass. For comparison, ACTs were also determined by a Hemochron Jr. Signature® and a Hepcon® HMS. The TEG® TF/K correlated with both the Hepcon (r2 = 0.789) and Hemochron (r2 = 0.743) ACTs. The average ACT after heparin was 319 ± 119 s (mean ± SD) for the TEG® TF/K compared with 624 ± 118 s for the Hepcon instrument. To evaluate the effects of hemodilution on TEG® TF/K and Hemochron assays, ACT assays were performed on blood diluted to 50% and titrated with heparin from 0 to 6 U/mL. Both instruments showed significant (P < 0.01) changes in the ACT-versus-heparin slope, but the 0 heparin intercept for the TEG® TF/K ACTs was not significantly changed (P = 0.292), in contrast to that for the Hemochron device (P = 0.041). Both instruments also indicated the same 1.3:1 ratio of protamine to heparin for optimum heparin neutralization, with increasing ACTs at ratios >2.6:1. The TEG® TF/K ACT assay rapidly monitors heparin anticoagulation, in addition to the capabilities of this instrument to monitor platelet function, clotting factors, and fibrinolysis.

Change: How Young Voters Interpreted the Messages Sent During the 2008 Presidential Election Season

Change became the mantra of the 2008 presidential campaign. During the primaries, Senators Clinton, McCain and Obama, as well as Governor Huckabee, all used the idea of change as part of their campaign rhetoric. During the general election campaign, both Obama and McCain continued using change as their slogan. This study sought to determine what the youth vote believed that change meant, both in an overall sense and as attributed to each of the candidates. The data for Study 1 were conducted before the March 4, 2008, primary, and the data for Study 2 were collected in October 2008. In Study 1, 784 undergraduates from six states and nine colleges and universities participated. In Study 2, there were 260 undergraduates who participated. The findings in both studies reveal that the candidates were effective in their use of the word change , as the respondents were able to differentiate between the different campaign messages. Analysis of the open-ended data found several overall categories of change, and subsequent analysis found that these categories were more relevant to certain demographics than others. A discussion of the findings as well as ideas for future research is discussed.

Predictors of body mass index in female parents whose children participate in a competitive, creative, problem-solving program

Background Recent findings from our research indicate that children participating in a creative afterschool program exhibit overall healthier lifestyle practices compared to the average US pediatric population. This observation led us to investigate the prevalence of overweight/obesity and lifestyle practices of their parents. Objective To determine the strongest predictors of weight status for female parents whose children were participating in such creative afterschool program. Design Surveyed subjects were parents of children who competed in the 2008 and 2009 Destination ImagiNation® Global Finals in Knoxville, Tennessee. A total of 4,608 children participated in data collection, with parental consent. For the combined 2 years, 1,118 parents, 87% of whom were females (n=1,032) completed online questionnaires, which were based on the Behavioral Risk Factor Surveillance System and included self-reported height, weight, dietary intake, physical activity, and socioeconomic status. The majority of this population was white, and less than 5% were African American or Hispanic. Results We report here results obtained for the female parents. Only 45.2% of these female parents were overweight/obese, compared to a national average of 64.1% reported by the National Health Nutrition Examination Surveys for 2007—2008. Furthermore, this population was significantly more physically active compared to national average. Most parents (76%) had completed a college degree and reported high incomes. Parents with the lowest income were the most obese in this population. Finally, we found a significant association between parent and child weight status. Conclusions These studies demonstrate that female parents of children who have healthy lifestyles were physically active, which likely accounts for the parents’ lower overweight/obesity rates. In addition to physical activity, income and percentage of calories from fat were all predictors of weight status.

Installing and Updating R

When you purchase SAS, WPS or SPSS, they sell you a “binary”version. That is one that the company has compiled for you from the “source code” version they wrote using languages such as C, FORTRAN, or Java. You usually install everything you purchased at once and do not give it a second thought. Instead, R is modular. The main installation provides Base R and a recommended set of add-on modules called packages. You can install other packages later when you need them. With thousands to choose from, few people need them all.

Managing Your Files and Workspace

Stata and R both have commands that replicate many of your computer’s operating system functions such as listing names of objects, deleting them, setting search paths, and so on. Learning how to use these commands is especially important because, like Stata, R stores its data in your computer’s limited random access memory. You need to make the most of your computer’s memory when handling large data sets or when a command is highly iterative.

Programming Language Basics

In this chapter we will go through the fundamental features in R. It will be helpful if you can download the book’s files from the Web site http://r4stats.com and run each line as we discuss it. Many of our examples will use our practice data set described in Sect. 1.7.

Selecting Variables and Observations

In the previous two chapters, we focused on selecting variables and observations separately. You can combine those approaches to select both variables and observations at the same time. As an example, we will use the various methods to select the variables workshop and q1 to q4 for only the males.