On the multivariate random and mixed coefficient analysis

The random coefficient and mixed effect model analyses are widely used as statistical techniques for repeated-measures design, panel data, and longitudinal studies. The interpretation of the analyses is based either on the traditional fixed-random effects approach or on the empirical Bayes approach. A general multi-response mixed coefficient model and its various special cases are considered in this dissertation. The existing statistical procedures for some special cases have some shortcomings. First, the estimation of the random coefficient covariance matrix does not take into account the complicated nature of the parameter space. This can be a serious practical problem when the fully random coefficient is assumed but its actual variability is limited, and when the resulting estimate is used for further analysis. An estimated covariance matrix needs to be nonnegative definite, and may possibly be singular of any rank. New maximum likelihood estimation and restricted maximum likelihood estimation algorithms with proper justification and with the parameter space consideration are proposed for various special cases of the general multivariate mixed coefficient model. Alternative non-iterative estimation methods are also proposed and discussed. All the estimation methods developed here produce a nonnegative definite estimated covariance matrix of any rank, and provide some insight into possible structure of the random coefficients;The second problem in the random or mixed coefficient analysis, which has not been studied satisfactorily, is that of determining coefficients or functions of coefficients to be treated as constant instead of random. For this problem, several new test procedures are introduced and their properties are compared. The idea here is the development of simple and useful test procedures that can be utilized in the model building stage of the analysis.</p

Algorithms for the likelihood-based estimation of the random coefficient model

The existing algorithms for fitting the random coefficient models tend to have difficulties associated with the covariance matrix parameter space. New ML and REML algorithms are developed, explicitly addressing the parameter space problem. Theoretical justification and numerical results are presented.Proper covariance matrix estimate Mixed effects Maximum likelihood REML

Long-term Effects of Universal Preventative Interventions on Methamphetamine Use among Adolescents

Setting  Public schools in the Midwest from 1993 to 2004.Participants  Study 1 began with 667 sixth grade students from 33 rural public schools; the follow-up included 457 students. Study 2 began with 679 seventh grade students from 36 rural public schools; the follow-up assessment included 597 students.Interventions  In study 1, schools were assigned to the Iowa Strengthening Families Program (ISFP), Preparing for the Drug Free Years, or a control condition. In study 2, schools were assigned to a revised ISFP (SFP 10-14) plus Life Skills Training (SPF 10-14 + LST), LST alone, or a control condition.Results  Self-reports of lifetime and past-year methamphetamine use were collected at 6½ years past baseline (study 1) and at 4½ and 5½ years past baseline (study 2). In study 1, the ISFP past-year rate was 0.0% compared with 3.2% in the control condition (P = .04). In study 2, SFP 10-14 + LST showed significant effects on lifetime and past-year use at the 4½ year follow-up (eg, 0.5% lifetime use in the intervention condition vs 5.2% in the control condition, P = .006); both SFP 10-14 + LST and LST alone had significant lifetime use effects at the 5½ year follow-up.Conclusion  Brief universal interventions have potential for public health impact by reducing methamphetamine use among adolescents

Long-term effects of universal preventive interventions on methamphetamine use among adolescents. Arch Pediatr Adolesc Med

ABSTRACT Background This is a supplemental report on tests of the long-term effects of universal preventive interventions conducted during middle school on 17-21-year-olds&apos; prescription drug misuse. Design/setting/participants Two randomized controlled prevention trials were conducted in public schools in the rural midwestern United States. Study 1 began in 1993, with 667 6th-graders; follow-ups with 12th-graders and 21-year-olds included 457 and 483 participants, respectively. Study 2 began in 1998 with 7th-graders (total sample across waves 2127); follow-ups with 11th-and 12th-graders included 1443 and 1212 participants, respectively. Interventions In study 1, schools were assigned to the Iowa Strengthening Families Program (ISFP), Preparing for the Drug Free Years, or a control condition. In study 2, schools were assigned to the school-based Life Skills Training (LST) plus a revised ISFP, called SFP 10-14 (LST + SFP 10-14), LST-only, or a control condition. Measurements Self reports of lifetime and past-year prescription drug misuse. Findings In study 1, ISFP 12th-graders&apos; past year narcotic misuse was significantly less than controls, as were ISFP 21-year-olds&apos; life-time narcotic and barbiturate misuse rates. In study 2, LST + SFP 10-14 showed significant effects on life-time prescription drug misuse at the 11th-grade follow-up, while effects at the 12th-grade follow-up were marginally significant. Conclusions Consistent with intervention effects on other substance use outcomes reported earlier, results suggest that universal interventions have potential for pubic health impact by reducing some types of prescription drug misuse among adolescents and young adults

Universal Intervention as a Protective Shield Against Exposure to Substance Use: Long-Term Outcomes and Public Health Significance

Objectives. We examined universal preventive intervention effects on adolescents' exposure to opportunities for substance use and on illicit substance use in the long term