Principles and Practice of Structural Equation Modeling (2nd ed.)

Man's Search for Meaning: An Introduction to Logotherapy.

EDITORIAL BOARD Robert Davison Aviles, Bradley University Harley E. Baker, California State University–Channel Islands Jean-Guy Blais, Universite de Montreal, Canada Catherine Y. Chang, Georgia State University Robert C. Chope, San Francisco State University Kevin O. Cokley, University of Missouri, Columbia Patricia B. Elmore, Southern Illinois University Shawn Fitzgerald, Kent State University John J. Fremer, Educational Testing Service Vicente Ponsoda Gil, Universidad Autonoma de Madrid, Spain Jo-Ida C. Hansen, University of Minnesota Charles C. Healy, University of California at Los Angeles Robin K. Henson, University of North Texas Flaviu Adrian Hodis, Victoria University of Wellington, New Zealand Janet K. Holt, Northern Illinois University David A. Jepsen, The University of Iowa Gregory Arief D. Liem, National Institute of Education, Nanyang Technological University Wei-Cheng J. Mau, Wichita State University Larry Maucieri, Governors State College Patricia Jo McDivitt, Data Recognition Corporation Peter F. Merenda, University of Rhode Island Matthew J. Miller, University of Maryland Ralph O. Mueller, University of Hartford Jane E. Myers, The University of North Carolina at Greensboro Philip D. Parker, University of Western Sydney Ralph L. Piedmont, Loyola College in Maryland Alex L. Pieterse, University at Albany, SUNY Nicholas J. Ruiz, Winona State University James P. Sampson, Jr., Florida State University William D. Schafer, University of Maryland, College Park William E. Sedlacek, University of Maryland, College Park Marie F. Shoffner, University of Virginia Len Sperry, Florida Atlantic University Kevin Stoltz, University of Mississippi Jody L. Swartz-Kulstad, Seton Hall University Bruce Thompson, Texas A&M University Timothy R. Vansickle, Minnesota Department of Education Steve Vensel, Palm Beach Atlantic University Dan Williamson, Lindsey Wilson College F. Robert Wilson, University of Cincinnati

measurement and evaluation in counseling and Development

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Applied Longitudinal Data Analysis Modeling Change And Event Occurrence

https://www.thelancet.com/pdfs/journals/lancet/PIIS0140-6736(12)60238-4.pdf

Worldwide application of prevention science in adolescent health

Although different methods are available for the analyses of longitudinal data, analyses based on generalized linear models (GLM) are criticized as violating the assumption of independence of observations. Alternatively, linear mixed models (LMM) are commonly used to understand changes in human behavior over time. In this paper, the basic concepts surrounding LMM (or hierarchical linear models) are outlined. Although SPSS is a statistical analyses package commonly used by researchers, documentation on LMM procedures in SPSS is not thorough or user friendly. With reference to this limitation, the related procedures for performing analyses based on LMM in SPSS are described. To demonstrate the application of LMM analyses in SPSS, findings based on six waves of data collected in the Project P.A.T.H.S. (Positive Adolescent Training through Holistic Social Programmes) in Hong Kong are presented.

/pdf/longitudinal-data-analyses-using-linear-mixed-models-in-spss-2q3rpz3pd1.pdf

Longitudinal Data Analyses Using Linear Mixed Models in SPSS: Concepts, Procedures and Illustrations

This paper examines the dimensionality and factorial invariance of the Chinese Positive Youth Development Scale (CPYDS) using multigroup confirmatory factor analyses (MCFA). Secondary 1 students (N = 5,649) responded to the CPYDS in the context of a positive youth development program. Results showed that there are 15 basic dimensions of the CPYDS which are subsumed under four higher-order factors (i.e., cognitive-behavioral competencies, prosocial attributes, positive identity and general positive youth development qualities). Evidence of factorial invariance in terms of configuration, first-order factor loadings, second-order factor loadings, intercepts of measured variable, and intercepts of first-order latent factor, was found. The findings suggest that the CPYDS has stable dimensions that can be used to assess positive youth development in Chinese adolescents.

/pdf/dimensionality-of-the-chinese-positive-youth-development-2bieesv4bp.pdf

Dimensionality of the Chinese Positive Youth Development Scale: Confirmatory Factor Analyses

Objective: This paper examines the dimensionality and factorial invariance of the Chinese Family Assessment Instrument (C-FAI) using multigroup confirmatory factor analyses (MCFAs). Method: A total of 3,649 students responded to the C-FAI in a community survey. Results: Results showed that there are five dimensions of the C-FAI (communication, mutuality, conflict and harmony, parental concern, parental control), which are subsumed under two higher order factors (family interaction and parenting). Evidence of factorial invariance in terms of configuration, first-order factor loadings, second-order factor loadings, intercepts of measured variable, and intercepts of first-order latent factor, was found. Conclusions: The C-FAI is an objective measure of Chinese family functioning with high factorial validity. It can be used in family practice contexts of Chinese families.

/pdf/the-chinese-family-assessment-instrument-c-fai-hierarchical-1potj32y82.pdf

The Chinese Family Assessment Instrument (C-FAI): Hierarchical Confirmatory Factor Analyses and Factorial Invariance

The Tier 1 Program of the Project P.A.T.H.S. (Positive Adolescent Training through Holistic Social Programs) is a positive youth development program implemented in school settings utilizing a curricular-based approach. In the third year of the Full Implementation Phase, 19 experimental schools (n = 3,006 students) and 24 control schools (n = 3,727 students) participated in a randomized group trial. Analyses based on linear mixed models via SPSS showed that participants in the experimental schools displayed better positive youth development than did participants in the control schools based on different indicators derived from the Chinese Positive Youth Development Scale, including positive self-identity, prosocial behavior, and general positive youth development attributes. Differences between experimental and control participants were also found when students who joined the Tier 1 Program and perceived the program to be beneficial were employed as participants of the experimental schools. The present findings strongly suggest that the Project P.A.T.H.S. is making an important positive impact for junior secondary school students in Hong Kong.

/pdf/impact-of-the-project-p-a-t-h-s-in-the-junior-secondary-1wiwms7l4b.pdf

Impact of the Project P.A.T.H.S. in the Junior Secondary School Years: Individual Growth Curve Analyses

To assess the effectiveness of the Tier 1 Program of the Project P.A.T.H.S., a randomized group trial with eight waves of data collected was carried out. At the fifth year of data collection, 19 experimental schools (n = 2, 662 students) and 24 control schools (n = 3, 272 students) participated in the study. Analyses based on individual growth curve modeling showed that participants in the experimental schools displayed better positive youth development than did participants in the control schools in terms of different indicators derived from the Chinese Positive Youth Development Scale, including moral competence and behavioral competence and cognitive behavioral competencies. Significant results were also found when examining the trajectories of psychological development among control and experimental participants who perceived the program to be beneficial. Findings based on longitudinal objective outcome evaluation strongly suggest that the Project P.A.T.H.S. is effective in promoting positive development in Hong Kong secondary school students.

/pdf/impact-of-the-project-p-a-t-h-s-in-the-junior-secondary-2gs93y99zr.pdf

Cecilia M. S. Ma

Papers

Longitudinal Data Analyses Using Linear Mixed Models in SPSS: Concepts, Procedures and Illustrations

Dimensionality of the Chinese Positive Youth Development Scale: Confirmatory Factor Analyses

The Chinese Family Assessment Instrument (C-FAI): Hierarchical Confirmatory Factor Analyses and Factorial Invariance

Impact of the Project P.A.T.H.S. in the Junior Secondary School Years: Individual Growth Curve Analyses

Impact of the Project P.A.T.H.S. in the junior secondary school years: objective outcome evaluation based on eight waves of longitudinal data.