Papers by Nicholas Horton
The American Journal of Drug and Alcohol Abuse, 2006
Utilization of emergency department (ED) services and hospitalization among a cohort of substance... more Utilization of emergency department (ED) services and hospitalization among a cohort of substance abusers are described based on structured research interviews with 470 adults without primary care admitted to an urban residential detoxification program. Cross-sectional analysis of baseline data of subjects found nearly 19% of subjects went to an ED on 2 or more occasions in the 6 months prior to detoxification and 14% were admitted for an overnight hospitalization. Upon further analysis of past 6-month ED utilization, the following factors were independently associated with increased odds of ED use: White race; at least one month homeless in the past 5 years chronic health condition; injury in past 6 months; and subject perception that their substance abuse interfered with seeking care from a regular doctor. Subjects with cocaine as a primary problem had lower odds of ED utilization than a reference group with alcohol as a primary problem.
This study examines the relationship between a history of physical and sexual abuse (PhySexAbuse)... more This study examines the relationship between a history of physical and sexual abuse (PhySexAbuse) and drug and alcohol related consequences. We performed a cross-sectional analysis of data from 359 male and 111 female subjects recruited from an inpatient detoxification unit. The Inventory of Drug Use Consequences (InDUC), measured negative life consequences of substance use. Eighty-one percent of women and 69%
Journal of Substance Abuse Treatment, 2002
This study examines the relationship between a history of physical and sexual abuse (PhySexAbuse)... more This study examines the relationship between a history of physical and sexual abuse (PhySexAbuse) and drug and alcohol related consequences. We performed a cross-sectional analysis of data from 359 male and 111 female subjects recruited from an inpatient detoxification unit. The Inventory of Drug Use Consequences (InDUC), measured negative life consequences of substance use. Eighty-one percent of women and 69% of men report past PhySexAbuse, starting at a median age of 13 and 11, respectively. In bivariate and multivariable analyses, PhySexAbuse was significantly associated with more substance abuse consequences ( p < 0.001). For men, age 17 years at first PhySexAbuse was significantly associated with more substance abuse consequences than an older age at first abuse, or no abuse ( p = 0.048). For women, the association of PhySexAbuse with substance use consequences was similar across all ages ( p = 0.59). Future research should develop interventions to lessen the substance abuse consequences of physical and sexual abuse. D
AIDS Research and Human Retroviruses, 2004
The HIV epidemic has been consistently associated with injection drug use and crack cocaine, but ... more The HIV epidemic has been consistently associated with injection drug use and crack cocaine, but alcohol problems in HIV-infected persons are less well described. Our objectives were 2-fold: (1) to assess the prevalence of alcohol problems in HIV-infected patients initiating medical care; and (2) to determine the positive predictive value of the CAGE questionnaire for alcohol abuse or dependence in HIV-infected patients. Between July 1997 and October 2000, we assessed a consecutive series of patients who were establishing primary care for HIV infection (clinic sample), using an established alcohol screening test, the CAGE questionnaire. In addition, we enrolled other HIV-infected patients, including some of the clinic sample, who had two or more positive responses to the CAGE questionnaire into a longitudinal cohort (cohort sample), performed a diagnostic interview for lifetime history of alcohol abuse and dependence, and determined the positive predictive value of CAGE for alcohol diagnoses. In the clinic sample (n = 664), 42% (276 of 664) had two or more positive responses to the four CAGE questions. In the cohort sample (n = 141), 95% (134 of 141) met DSM-IV criteria for diagnosis of lifetime alcohol abuse or dependence. For patients initiating HIV primary care, a history of alcohol problems is very common. The CAGE questionnaire identifies a lifetime history of alcohol abuse or dependence in HIV-infected patients. Routine screening for alcohol problems should be performed in all patients entering HIV medical care and the CAGE questions are useful in this setting.
Archives of Internal Medicine, 2009
Background: University students drink more heavily than their nonstudent peers and are often unaw... more Background: University students drink more heavily than their nonstudent peers and are often unaware that their drinking is risky and exceeds normative levels. We tested the efficacy of a proactive Web-based alcohol screening and brief intervention program.
Mathematical Thinking and Learning, 2011
Amstat News the Membership Magazine of the American Statistical Association, 2012
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... Berkeley and the London School of Economics for feedback helping to improve the second editio... more ... Berkeley and the London School of Economics for feedback helping to improve the second edition, and Charlie Hallahan, Nick Horton, Thomas Loughlin, and Rory Wolfe, among ... Data were provided in this form by D. Altman, M. Bland, G. Koch, S. MacNab, R. Mare, and P. Sham ...
Amer Statist, 2006
... Berkeley and the London School of Economics for feedback helping to improve the second editio... more ... Berkeley and the London School of Economics for feedback helping to improve the second edition, and Charlie Hallahan, Nick Horton, Thomas Loughlin, and Rory Wolfe, among ... Data were provided in this form by D. Altman, M. Bland, G. Koch, S. MacNab, R. Mare, and P. Sham ...
Abstract A nondisclosure policy for tabular data or microdata restricts release of information th... more Abstract A nondisclosure policy for tabular data or microdata restricts release of information that could be related to a specific individual. Pannekoek and de Waal (1998) describe a rule that suppresses data release when the number of people in a cell defined by a rare characteristic falls below a fixed floor, and show how empirical Bayes methods can be used
Learning R is a gradual process, and getting off to a good start goes a long way toward ensuring ... more Learning R is a gradual process, and getting off to a good start goes a long way toward ensuring success. In this monograph we discuss some strategies and tactics for getting started teaching statistics with R.
To assess clinician attitudes toward biostatistics at an academic medical center. We conducted a ... more To assess clinician attitudes toward biostatistics at an academic medical center. We conducted a cross-sectional survey of medical students, internal medicine resident physicians, and internal medicine teaching faculty at Mayo Clinic College of Medicine in Rochester, MN, in April 2005. Of 468 eligible participants, 301 (64.3 percent) responded to the survey. A total of 87.3 percent of respondents (262/300) believed it would benefit their career to better understand biostatistics, but only 17.6 percent (53/301) believed their training in biostatistics was adequate for their needs. A total of 23.3 percent of respondents (70/ 300) agreed they could identify when correct statistical methods had been applied in a study, 28.0 percent (84/300) agreed they could design their own research projects with confidence, and 14.6 percent (44/301) agreed they could conduct their own statistical analyses with confidence. Respondents with the highest self-reported level of statistical education and research experience were more likely to report these skills (all, P less than .001). A total of 92.7 percent of respondents (279/301) believed biostatistics is an important part of evidence-based medicine (EBM), and 88.0 percent (265/301) believed EBM is important for clinical practice. However, biostatistics was not evaluated as being as important as many other areas of study within medicine.
BMJ, 2013
Dropout in randomised controlled trials is common and threatens the validity of results, as compl... more Dropout in randomised controlled trials is common and threatens the validity of results, as completers may differ from people who drop out. Differing dropout rates between treatment arms is sometimes called differential dropout or attrition. Although differential dropout can bias results, it does not always do so. Similarly, equal dropout may or may not lead to biased results. Depending on the type of missingness and the analysis used, one can get a biased estimate of the treatment effect with equal dropout rates and an unbiased estimate with unequal dropout rates. We reinforce this point with data from a randomised controlled trial in patients with renal cancer and a simulation study.
BMC MEDICAL RESEARCH METHODOLOGY, 2007
Background: Alcohol consumption is commonly used as a primary outcome in randomized alcohol treat... more Background: Alcohol consumption is commonly used as a primary outcome in randomized alcohol treatment studies. The distribution of alcohol consumption is highly skewed, particularly in subjects with alcohol dependence.
In this tutorial, we describe regression-based methods for analysing multiple source data arising... more In this tutorial, we describe regression-based methods for analysing multiple source data arising from complex sample survey designs. We use the term 'multiple-source' data to encompass all cases where data are simultaneously obtained from multiple informants, or raters (e.g. self-reports, family members, health care providers, administrators) or via di erent=parallel instruments, indicators or methods (e.g. symptom rating scales, standardized diagnostic interviews, or clinical diagnoses). We review regression models for analysing multiple source risk factors or multiple source outcomes and show that they can be considered special cases of generalized linear models, albeit with correlated outcomes. We show how these methods can be extended to handle the common survey features of stratiÿcation, clustering, and sampling weights. We describe how to ÿt regression models with multiple source reports derived from complex sample surveys using general purpose statistical software. Finally, the methods are illustrated using data from two studies: the Stirling County Study and the Eastern Connecticut Child Survey.
Canadian Journal of Psychiatry Revue Canadienne De Psychiatrie, Dec 1, 2010
Objective-The question addressed is whether a mortality risk associated with depression in a 1952... more Objective-The question addressed is whether a mortality risk associated with depression in a 1952 representative sample of Stirling County adults changed in a new sample of 1970 and whether there was a change in relationships to cigarette smoking and alcoholism.
A growing number of students are completing undergraduate degrees in statistics and entering the ... more A growing number of students are completing undergraduate degrees in statistics and entering the workforce as data analysts. In these positions, they are expected to understand how to utilize databases and other data warehouses, scrape data from Internet sources, program solutions to complex problems in multiple languages, and think algorithmically as well as statistically. These data science topics have not traditionally been a major component of undergraduate programs in statistics. Consequently, a curricular shift is needed to address additional learning outcomes. The goal of this paper is to motivate the importance of data science proficiency and to provide examples and resources for instructors to implement data science in their own statistics curricula. We provide case studies from seven institutions. These varied approaches to teaching data science demonstrate curricular innovations to address new needs. Also included here are examples of assignments designed for courses that foster engagement of undergraduates with data and data science.
Amer J Psychiat, 2003
Building on findings about the prevalence and incidence of depression over a 40-year period, the ... more Building on findings about the prevalence and incidence of depression over a 40-year period, the authors provide data on trends in cigarette smoking and associations with depression. Data come from interviews with adult population samples (1952, 1970, and 1992) and followed cohorts (1952-1970 and 1970-1992). Logistic regression models and survival regressions were used to analyze the data. The associations between smoking and depression were small and nonsignificant in 1952 and 1970. In 1992, however, the odds that a smoker would be depressed were three times the odds that a nonsmoker would be depressed. The interaction between smoking and study year was significant, indicating that the association was limited to the most recent sample. In the cohort analysis, smoking at baseline did not predict the onset of depression, but subjects who became depressed were more likely to start or continue smoking and less likely to quit than those who never had a depression. In terms of population trends, the association between depression and cigarette smoking became prominent as the use of tobacco declined because of awareness of the risks involved. The findings about individuals followed over time suggest that those who became depressed were more involved with nicotine than those who never had a depression. The authors discuss hypotheses involving &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;self-medication,&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; risk-taking, and changes in the social climate but conclude that the relationships between smoking and depression are probably multiple and complex.
Statistics students need to develop the capacity to make sense of the staggering amount of inform... more Statistics students need to develop the capacity to make sense of the staggering amount of information collected in our increasingly data-centered world. Data science is an important part of modern statistics, but our introductory and second statistics courses often neglect this fact. This paper discusses ways to provide a practical foundation for students to learn to "compute with data" as defined by Nolan and Temple Lang (2010), as well as develop "data habits of mind" (Finzer, 2013). We describe how introductory and second courses can integrate two key precursors to data science: the use of reproducible analysis tools and access to large databases. By introducing students to commonplace tools for data management, visualization, and reproducible analysis in data science and applying these to real-world scenarios, we prepare them to think statistically in the era of big data.
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Papers by Nicholas Horton