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Jonathan L Blitstein

Publications and source records attributed to Jonathan L Blitstein.

14 recordsLinked to original sources
PubMed2007

Sizing a trial to alter the trajectory of health behaviours: methods, parameter estimates, and their application.

Group-randomized trials often involve repeat observations on the same participants. When there are no more than two observations from each participant, standard mixed-model regression methods for a pretest-posttest design can be used. When there are more than two observations from each participant, random coefficients models may be useful. This paper describes the random coefficients analysis appropriate to data from an extended nested cohort design and presents the methods for power analysis and sample size calculations based on that analysis. We provide estimates for the parameters required for those calculations for a number of adolescent health behaviours. We also show how the estimates can be used to plan a future trial.

Adolescent↗
PubMed2006

A comparison of permutation and mixed-model regression methods for the analysis of simulated data in the context of a group-randomized trial.

Our first purpose was to determine whether, in the context of a group-randomized trial (GRT) with Gaussian errors, permutation or mixed-model regression methods fare better in the presence of measurable confounding in terms of their Monte Carlo type I error rates and power. Our results indicate that given a proper randomization, the type I error rate is similar for both methods, whether unadjusted or adjusted, even in small studies. However, our results also show that should the investigator face the unfortunate circumstance in which modest confounding exists in the only realization available, the unadjusted analysis risks a type I error; in this regard, there was little to distinguish the two methods. Finally, our results show that power is similar for the two methods and, not surprisingly, better for the adjusted tests. Our second purpose was to examine the relative performance of permutation and mixed-model regression methods in the context of a GRT when the normality assumptions underlying the mixed model are violated. Published studies have examined the impact of violation of this assumption at the member level only. Our findings indicate that both methods perform well when the assumption is violated so long as the ICC is very small and the design is balanced at the group level. However, at ICC>or=0.01, the permutation test carries the nominal type I error rate while the model-based test is conservative and so less powerful. Binomial group- and member-level errors did not otherwise change the relative performance of the two methods with regard to confounding.

Computer Simulation↗
PubMed2006

Ethnic differences in predictors of adolescent smoking onset and escalation: a longitudinal study from 7th to 12th grade.

The present study sought to determine whether risk factors for cigarette smoking onset have a stronger influence on Black versus White children, and whether those patterns differ for nonsmokers versus experimental smokers. As part of a larger study, 5,213 seventh graders were surveyed annually for 5 years. The survey instrument assessed cigarette smoking, along with a variety of background variables thought to influence smoking. Results indicated that rebelliousness predicted smoking onset for Black nonsmokers; peer modeling was more influential for Whites. For both ethnicities, socially isolated children were at increased risk. The variables that predicted the shift from experimental to regular smoking were for the most part different from those that predicted smoking onset. Specifically, youths who lived with smokers, viewed smoking as a means to a goal, and experienced few adverse physiological effects of smoking were more likely to increase their cigarette consumption. Overall, we found that, contrary to previous research, risk factors for smoking differed across ethnicity. Further, smoking onset appears to be shaped by forces different from those that accelerate consumption.

Adolescent↗
PubMed2005

Increasing the degrees of freedom in existing group randomized trials: the df* approach.

This study describes a method for incorporating external estimates of intraclass correlation to improve the precision for the analysis of an existing group-randomized trial. The authors use a random-effects meta-analytic approach to pool the information across studies, which takes into account any interstudy heterogeneity that may exist. This approach can be used in several different situations to estimate the degrees of freedom available for an adjusted test of the intervention effect in a study where the challenges of group-randomized trials were not fully considered when the study was planned. The authors discuss the limitations of this approach and the circumstances in which it is likely to be helpful.

Humans↗
PubMed2005

Increasing the degrees of freedom in future group randomized trials: the df* approach.

This article builds on the previous article by Blitstein et al. (2005), which showed how external estimates of intraclass correlation can be used to improve the precision for the analysis of an existing group randomized trial. The authors extend that work to sample size estimation and power analysis for future group-randomized trials. Often this approach will allow a smaller study than would otherwise be possible without sacrificing statistical power. Such studies are needed, for example, as pilot studies to help plan for a full-scale efficacy trial, as replication studies, or in situations in which resource constraints prohibit a larger trial. The authors discuss the circumstances under which this strategy will be most helpful and the risks associated with conducting smaller studies.

Humans↗
PubMed2005

Predictors of violent behavior in an early adolescent cohort: similarities and differences across genders.

The authors assessed a cohort of 2,335 students from the Minneapolis, Minnesota, area to identify predictors of violent behavior and to determine whether the predictors varied by gender. The sample was 76% White; boys and girls were equally represented. The majority lived with two parents. A measure of violent behavior collected at the end of the eighth-grade year (2000) was entered into Poisson regression against baseline data collected at the beginning of the seventh-grade year (1998). Predictors of violent behavior influencing both boys and girls included depressive symptoms, perceived invulnerability to negative future events, paternal nonauthoritative behavior, and drinking alcohol. Additional predictors of violent behavior specific to girls included both risk and protective factors.

Adolescent↗
PubMed2004

Assessing the most powerful analysis method for school-based intervention studies with alcohol, tobacco, and other drug outcomes.

This article compares four mixed-model analyses valid for group-randomized trials (GRTs) involving a nested cohort design with a single pretest and a single posttest, the most common design used in GRTs. This study makes estimates of intraclass correlations (ICCs) available to investigators planning GRTs with alcohol, tobacco, and other drug measures as the outcomes of interest. It also provides formulae demonstrating the potential benefits to the standard error of the intervention effect of both adjustments for fixed and time-varying covariates, as well as correlations over time. These estimates will allow other researchers using these variables to plan their studies by performing a priori power analyses for any of four common analytic options.

Adolescent↗
PubMed2004

Assessing intervention effects in a school-based nutrition intervention trial: which analytic model is most powerful?

This article compares four mixed-model analyses valid for group-randomized trials (GRTs) involving a nested cohort design with a single pretest and posttest. This study makes estimates of intraclass correlations (ICCs) available to investigators planning GRTs addressing dietary outcomes. It also provides formulae demonstrating the potential benefits to the standard error of the intervention effect (sigma(delta)) from adjustments for both fixed and time-varying covariates and correlations over time. These estimates will allow other researchers using these variables to plan their studies by estimating a priori detectable differences and sample size requirements for any of the four analytic options. These methods are demonstrated using data from the Teens Eating for Energy and Nutrition at School study. Mixed-model analyses of covariance proved to be the most powerful analysis in that data set. The formulae may be applied to any dependent variable in any GRT given corresponding information for those variables on the parameters that define the formulae.

Adolescent↗
PubMed2004

Design and analysis of group-randomized trials: a review of recent practices.

We reviewed group-randomized trials (GRTs) published in the American Journal of Public Health and Preventive Medicine from 1998 through 2002 and estimated the proportion of GRTs that employ appropriate methods for design and analysis. Of 60 articles, 9 (15.0%) reported evidence of using appropriate methods for sample size estimation. Of 59 articles in the analytic review, 27 (45.8%) reported at least 1 inappropriate analysis and 12 (20.3%) reported only inappropriate analyses. Nineteen (32.2%) reported analyses at an individual or subgroup level, ignoring group, or included group as a fixed effect. Hence increased vigilance is needed to ensure that appropriate methods for GRTs are employed and that results based on inappropriate methods are not published.

Bibliometrics↗
PubMed2004

Design and analysis of group-randomized trials: a review of recent methodological developments.

We review recent developments in the design and analysis of group-randomized trials (GRTs). Regarding design, we summarize developments in estimates of intraclass correlation, power analysis, matched designs, designs involving one group per condition, and designs in which individuals are randomized to receive treatments in groups. Regarding analysis, we summarize developments in marginal and conditional models, the sandwich estimator, model-based estimators, binary data, survival analysis, randomization tests, survey methods, latent variable methods and nonlinear mixed models, time series methods, global tests for multiple endpoints, mediation effects, missing data, trial reporting, and software. We encourage investigators who conduct GRTs to become familiar with these developments and to collaborate with methodologists who can strengthen the design and analysis of their trials.

Cluster Analysis↗
PubMed2003

Rapid progression to regular cigarette smoking among nonsmoking adolescents: interactions with gender and ethnicity.

BACKGROUND: While the correlates and predictors associated with transition through the stages of smoking acquisition have received substantial attention, the identification of factors associated with the time course of progression remain generally unexplored. METHODS: We identified adolescents escalating from nonsmoking to regular smoking in 1 year as rapid progressors (n = 98) and those escalating from nonsmoking to experimental smoking in 1 year as slow progressors (n = 555). We entered demographic and psychosocial variables, initial reactions to smoking variables, and their interactions with gender and ethnicity into a logistic regression analysis comparing rapid progressors to slow progressors. RESULTS: At baseline, rapid progressors reported more friends who smoked regularly. Girls who reported more concern with dieting and less social success were more likely to progress to regular smoking within 1 year; these variables did not influence progression in boys. Those who associated positive feelings with their initial smoking experience were more likely to progress to regular smoking. Differences between white and African American youth emphasize the importance of physiological interpretations of initial smoking experiences. CONCLUSIONS: Our findings suggest that even as nonsmokers, adolescents likely to progress quickly to regular smoking can be identified. Researchers designing prevention programs should take these factors into account.

Adolescent↗
PubMed2003

The reliability and predictive value of adolescents' reports of initial reactions to smoking.

A sample of 372 adolescents completed annual surveys regarding their initial reactions to smoking (IRTS) and their current smoking status. Each annual survey asked participants if they had the following five reactions the first time they smoked a cigarette: coughing, or feeling dizzy, sick, high, or relaxed. Time 1 IRTS data were collected within 1 year of the reported initial smoking experience, and Time 2 IRTS data were collected 1 year later. Kappa values for two IRTS items, coughing (.45) and dizziness (.40), indicated modest but acceptable reliability across a 1-year period, but the remaining items showed poor reliability (all < or =.31). Logistic regression analyses indicated that no IRTS item significantly predicted regular (at least weekly) smoking 1 year later. However, when IRTS and smoking status were assessed concurrently (at Time 2), reports of feeling relaxed and not coughing during the initial episode were significantly correlated with regular smoking. Participants who progressed from experimental to regular smoking from Time 1 to Time 2 were more likely to report relaxation as an initial reaction to smoking at Time 2 after denying relaxation at Time 1.

Adolescent↗
PubMedDate not supplied

Use of nutrition facts panels among adults who make household food purchasing decisions.

OBJECTIVE: To identify sociodemographic variables and beliefs about the causes of obesity associated with reported use of Nutrition Facts panel (NFP) information. DESIGN/SETTING: Nationally representative, cross-sectional survey of 1139 adults. Data collection employed a single-stage, equal-probability sampling design with random-digit dialing across 50 states and the District of Columbia. Analysis sample consisted of 390 adults living with one or more children who reported making food purchasing decisions. MAIN OUTCOME MEASURE: Respondents provided self-reported information on their use of NFP information when making food purchasing decisions for their household. ANALYSIS: Chi-square and analysis of variance (ANOVA) tests compared the analysis sample to the broader population. Logistic regression analyses identified the sociodemographic and beliefs about obesity variables related to NFP use. RESULTS: Fifty-three percent of the sample reported using NFP information on a consistent basis. Females, those with more education, and those currently married were more likely to use NFP labels. The importance of knowledge in order to maintain healthy body weight was the only belief variable associated with use of NFP information. IMPLICATIONS FOR RESEARCH AND PRACTICE: Nutrition educators interested in changing dietary behaviors should begin by identifying levels of nutritional literacy and beliefs about the importance of nutrition to motivate use of NFP labels.

Adult↗