Terry E. Duncan

Oregon Research Institute

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Susan C. Duncan

St. Joseph Hospital

Lisa A. Strycker

Oregon Department of Education

Fuzhong Li

Oregon Research Institute

Hyman Hops

Marquette University

Edward McAuley

University of Kansas Medical Center

Nigel R. Chaumeton

Oregon Research Institute

Peter Harmer

Oregon Research Institute

Mike Stoolmiller

Oregon Research Institute

Dennis V. Ary

Oregon Center For Applied Science (United States)

Alan C. Acock

John Wiley & Sons (United States)

Cooperative Institutions

Oregon Research Institute

Eugene Research Institute

University of Oregon

Oregon Health & Science University

University of Washington

Oregon Social Learning Center

University of Illinois Urbana-Champaign

Oregon Department of Education

Arizona State University

Oregon Center For Applied Science (United States)

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Multivariate Representations of Growth and Development

Routledge eBooks (2013)

Terry E. Duncan Susan C. Duncan Lisa A. Strycker

10.4324/9780203879962-4

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Modeling Incomplete Longitudinal Substance Use Data Using Latent Variable Growth Curve Methodology

Multivariate Behavioral Research (1994)

Susan C. Duncan Terry E. Duncan

Abstract Longitudinal data sets typically suffer from attrition and other forms of missing data. When this common problem occurs, several researchers have demonstrated that correct maximum likelihood estimation with missing data can be obtained under mild assumptions concerning the missing data mechanism. With reasonable substantive theory, a mixture of cross-sectional and longitudinal methods developed within multiple-group structural equation modeling can provide a strong basis for inference about developmental change. Using an approach to the analysis of missing data, the present study investigated developmental trends in adolescent (N = 759) alcohol, marijuana, and cigarette use across a 5-year period using multiple-group latent growth modeling. An associative model revealed that common developmental trends existed for all three substances. Age and gender were included in the model as predictors of initial status and developmental change. Findings discuss the utility of latent variable structural equation modeling techniques and missing data approaches in the study of developmental change.

Latent growth modeling

Longitudinal data

Growth curve (statistics)

10.1207/s15327906mbr2904_1

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Citations (113)

A Multilevel Analysis of Sibling Physical Activity

Journal of Sport and Exercise Psychology (2004)

Susan C. Duncan Terry E. Duncan Lisa A. Strycker Nigel R. Chaumeton

Typical studies of youth physical activity ignore the dependence among family members, examining only individual levels of data rather than individual and family levels. The current study examined physical activity among siblings (mean age = 12.2 years), using hierarchical linear modeling. Individual-and family-level covariates of physical activity were included in the model. Data from 930 siblings nested within 371 families were analyzed in a four-level multilevel design. Results indicated that siblings were similar in their levels of physical activity, and that levels of physical activity varied across families. At the individual level, age was a significant predictor of physical activity. At the family level, higher levels of family support were related to higher levels of sibling physical activity, as were single-parent status and higher income. Perceptions of neighborhood opportunities and observed neighborhood physical activity facilities were negatively related to family levels of physical activity.

10.1123/jsep.26.1.57

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Citations (58)

Tai Chi Enhances Self-Efficacy and Exercise Behavior in Older Adults

Journal of Aging and Physical Activity (2001)

Fuzhong Li Edward McAuley Peter Harmer Terry E. Duncan Nigel R. Chaumeton

The article describes a randomized, controlled trial conducted to examine the effects of a Tai Chi intervention program on perceptions of personal efficacy and exercise behavior in older adults. The sample comprised 94 low-active, healthy participants (mean age = 72.8 years. SD = 5.1) randomly assigned to either an experimental (Tai Chi) group or a wait-list control group. The study length was 6 months, with self-efficacy responses (barrier, performance efficacies) assessed at baseline, at Week 12, and at termination (Week 24) of the study. Exercise attendance was recorded as an outcome measure of exercise behavior. Random-effects models revealed that participants in the experimental group experienced significant improvements in self-efficacy over the course of the intervention. Subsequent repeated-measures ANOVA revealed that participants’ changes in efficacy were associated with higher levels of program attendance. The findings suggest that self-efficacy can be enhanced through Tai Chi and that the changes in self-efficacy are likely to improve exercise adherence.

Self-Efficacy

Attendance

Repeated measures design

10.1123/japa.9.2.161

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Citations (86)

Tai Chi as a Means to Enhance Self-Esteem: A Randomized Controlled Trial

Journal of Applied Gerontology (2002)

Fuzhong Li Peter Harmer Nigel R. Chaumeton Terry E. Duncan Susan C. Duncan

Using a randomized controlled trial, this study examined whether a 6-month Tai Chi exercise program enhanced elderly individuals' multidimensional, hierarchical physical self-esteem. Participants either continued their daily routine activities or participated in a Tai Chi exercise class performing slow rhythmic movements. Both global and domain-specific physical esteem measures were assessed at baseline, at 3 months, and at the 6-month termination of the intervention. Growth curve models were used to analyze the repeated-measures data. Results indicated that individuals who participated in the 6-month Tai Chi exercise program showed increased levels of global self-esteem, domain-specific physical self-worth, and subdomain-specific esteem of attractive body, physical strength, and physical condition. Thus, Tai Chi, a simple, low-cost form of physical activity, has the potential to alter favorably specific facets of physical self-worth/ esteem in older adults, which may in turn enhance important aspects of their quality of life.

10.1177/073346480202100105

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Citations (60)

Landing a Horizontal Well with the Assistance of 2D VSP

Proceedings (2013)

Simon Berman Vladislav Lesnikov Terry E. Duncan Richard G. Williams

This paper describes the uncertainties associated with determining an appropriate dip to geosteer a well towards the landing zone and along the well trajectory, and how a 2D VSP helped. Various methods of pre-drill dip estimation are discussed and compared to the 2D VSP and to LWD measurements.

10.3997/2214-4609.20142573

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Multilevel covariance structure analysis of sibling antisocial behavior

Structural Equation Modeling A Multidisciplinary Journal (1998)

Terry E. Duncan Anthony Alpert Susan C. Duncan

Conventional covariance structure analysis, such as factor analysis, is often applied to data that are obtained in a hierarchical fashion, such as siblings observed within families. Multivariate modeling of such data, however, is most frequently done as if the data were obtained as a simple random sample from a single population. An alternative specification is presented that explicitly models the within‐level and between‐level covariance matrices in familial antisocial behavior. Sibling data from the National Youth Survey, a national probability sample of youth, were used to specify a multilevel covariance structure analysis of sibling antisocial behavior. Results demonstrate homogeneity in antisocial behavior within sibling clusters but heterogeneity across families. These analyses highlight potential pitfalls of ignoring issues of independence and demonstrate how conventional covariance structure software can be easily adapted to handle hierarchical models, providing a large set of new analysis possibilities for multilevel data.

Analysis of covariance

10.1080/10705519809540102

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Citations (14)

Parent substance use as a predictor of adolescent use: A six-year lagged analysis

Annals of Behavioral Medicine (1996)

Hyman Hops Terry E. Duncan Susan C. Duncan Michael Stoolmiller

The present study investigated the role of parental use of alcohol, cigarettes, and marijuana on lagged changes in the specific substance use of their adolescent offspring over a six-year period. The analyses also examined the relative influence of mothers and fathers and their interaction as moderated by marital status and age and gender of the adolescent. A generalized estimating equations approach, analogous to quasi-like-lihood, was employed to estimate regression coefficients via an iterative weighted least squares algorithm. Findings indicated that, when employed as time-varying covariates, parental substance use resulted in substance-specific effects on fluctuations in the adolescent's own use. Age, parent marital status, and each parent's marijuana use independently were jound to significantly affect adolescent marijuana use. In contrast, the complex relationship between parent and adolescent use of alcohol and cigarettes showed variation by substance, age, and gender of both parents and adolescents. Within a developmental context, the results suggest that parent use of substances must be considered risk factors with particular effects on their younger offspring. Thus, prevention efforts should be directed at middle childhood and include components aimed at parents as well as their children.

Health psychology

10.1007/bf02883392

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Citations (76)

Analysis of longitudinal data within accelerated longitudinal designs.

Psychological Methods (1996)

Susan C. Duncan Terry E. Duncan Hyman Hops

Longitudinal data

Longitudinal Study

Statistical Analysis

10.1037/1082-989x.1.3.236

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