NotesFAQContact Us
Collection
Advanced
Search Tips
Showing 11,956 to 11,970 of 18,014 results Save | Export
Peer reviewed Peer reviewed
Blaha, John; Merydith, Scott P.; Wallbrown, Fred H.; Dowd, Thomas E. – Measurement and Evaluation in Counseling and Development, 2001
A hierarchical factor solution on the Minnesota Multiphasic Personality Inventory-2 standardization sample found a general psychopathology factor and four primary factors similar to those reported by Butcher, Dahlstrom, Graham, Tellegen, and Kaemmer (1989). (Contains 29 references and 2 tables.) (Author)
Descriptors: Factor Analysis, Factor Structure, Personality Measures, Psychopathology
Peer reviewed Peer reviewed
Lanning, Kevin – Multivariate Behavioral Research, 1996
Effects of sample size and composition are systematically examined on the replicability of principal components, using observer ratings of personality from the California Adult Q-Set for 192 series of principal components analyses. Results indicate that dimensionality cannot be inferred from component robustness; they are empirically and logically…
Descriptors: Factor Analysis, Personality Measures, Robustness (Statistics), Sample Size
Peer reviewed Peer reviewed
Jackson, Stacy L.; And Others – Journal of Career Assessment, 1996
Factor analysis of 1,030 adults' responses on the Myers Briggs Type Indicator (MBTI) were used to test 4 alternative models. Results support a four-factor structure similar to the original Jungian structure. Elimination of 12 MBTI items was recommended. (SK)
Descriptors: Construct Validity, Factor Analysis, Models, Personality Measures
Peer reviewed Peer reviewed
Hayduk, Leslie A.; Glaser, Dale N. – Structural Equation Modeling, 2000
Focuses on the four-step method (four nested models) of structural equation modeling advocated by S. Mulaik (1997, 1998), discussing the limitations of the approach and considering the tests and criteria to be used in moving among the four steps. (SLD)
Descriptors: Factor Analysis, Factor Structure, Research Methodology, Structural Equation Models
Peer reviewed Peer reviewed
Mulaik, Stanley A.; Millsap, Roger E. – Structural Equation Modeling, 2000
Defends the four-step approach to structural equation modeling based on testing sequences of models and points out misunderstandings of opponents of the approach. The four-step approach allows the separation of respective constraints within a structural equation model. (SLD)
Descriptors: Factor Analysis, Factor Structure, Research Methodology, Structural Equation Models
Peer reviewed Peer reviewed
Bollen, Kenneth A. – Structural Equation Modeling, 2000
Neither the four-step model nor the one-step procedure can actually tell whether the researcher has the right number of factors in structural equation modeling. In fact, for reasons discussed, a simple formulaic approach to the correct specification of models does not yet exist. (SLD)
Descriptors: Factor Analysis, Factor Structure, Research Methodology, Structural Equation Models
Peer reviewed Peer reviewed
Hayduk, Leslie A.; Glaser, Dale N. – Structural Equation Modeling, 2000
Replies to commentaries on the four-step approach to structural equation modeling, pointing out the strengths and weaknesses of each argument and ultimately concluding that the four-step model is subject to criticisms that can be addressed to factor analysis as well. (SLD)
Descriptors: Factor Analysis, Factor Structure, Research Methodology, Structural Equation Models
Peer reviewed Peer reviewed
Ruggiero, Kenneth J.; Morris, Tracy L.; Beidel, Deborah C.; Scotti, Joseph R.; McLeer, Susan V. – Assessment, 1999
Examined the discriminant validity of the State-Trait Anxiety Inventory for Children (C. Spielberger, 1973) and the Children's Depression Inventory (M. Kovacs, 1992) using a sample of 240 clinic-referred and non-clinic-referred children aged 8 to 14 years. Factor analysis yielded distinct factors of anxiety and depression. (SLD)
Descriptors: Adolescents, Anxiety, Children, Depression (Psychology)
Peer reviewed Peer reviewed
Direct linkDirect link
McDonald, Roderick P. – Structural Equation Modeling: A Multidisciplinary Journal, 2005
The use of an independent clusters basis for restricted factor analysis can be recommended in cases where the known structure of a subset of variables serves to determine the structure of the remaining variables in the set. A comparison of this technique with an appropriate form of restricted factor analysis is illustrated on a large set of…
Descriptors: Factor Analysis, Depression (Psychology), College Students, Anxiety
Peer reviewed Peer reviewed
Ott, Carol H.; Cashin, Susan E.; Altekruse, Michael – Journal of American College Health, 2005
The authors report on the development and assessment of an instrument to measure baseline campus cigarette use and outcomes from prevention programs, including those using a social norms approach combined with environmental policy change. They administered the 37-item College Tobacco Survey (CTS) to a convenience sample of 1,279 college students…
Descriptors: Prevention, Urban Universities, Smoking, Norms
Peer reviewed Peer reviewed
Dumenci, Levent; Erol, Nese; Achenbach, Thomas M.; Simsek, Zeynep – Journal of Abnormal Child Psychology, 2004
The new correlated 8-factor measurement structure of the Child Behavior Checklist for ages 6-18 (CBCL/6-18; T. M. Achenbach & L. A. Rescorla, 2001) derived from an American sample was used as a benchmark to evaluate its generalizability to Turkish general population (N = 5, 195) and clinical (N = 963) samples. Item-level confirmatory factor…
Descriptors: Psychometrics, Child Behavior, Check Lists, Factor Analysis
Peer reviewed Peer reviewed
Atherly, Adam; Kane, Robert L.; Smith, Maureen A. – Gerontologist, 2004
Purpose: The objective of this study is to develop an instrument to evaluate satisfaction with care for older adults in capitated environments. Although satisfaction with care is now widely accepted as an important outcome measure, there are relatively few satisfaction measures developed or validated on older persons. Because many older persons…
Descriptors: Validity, Family Involvement, Factor Analysis, Parent Participation
Peer reviewed Peer reviewed
Direct linkDirect link
Lee, Sik-Yum; Song, Xin-Yuan; Skevington, Suzanne; Hao, Yua-Tao – Structural Equation Modeling, 2005
Quality of life (QOL) has become an important concept for health care. As QOL is a multidimensional concept that is best evaluated by a number of latent constructs, it is well recognized that latent variable models, such as exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) are useful tools for analyzing QOL data. Recently,…
Descriptors: Questionnaires, Quality of Life, Factor Analysis, Structural Equation Models
Peer reviewed Peer reviewed
Rosen-Grandon, Jane R.; Myers, Jane E.; Hattie, John A. – Journal of Counseling and Development, 2004
Structural Equation Modeling techniques were used to clarify the relationship between marital characteristics, marital processes, and the dependent variable--marital satisfaction--in a sample of 201 participants who were in 1st marriages. The Dyadic Adjustment Scale (DAS; G. B. Spanier, 1976) and the Enriching and Nurturing Relationship Issues,…
Descriptors: Interaction, Structural Equation Models, Factor Analysis, Marital Satisfaction
Peer reviewed Peer reviewed
Direct linkDirect link
Bloch, George J.; Neeleman, Lori; Aleamoni, Lawrence M. – Assessment, 2004
High stress is known to affect health, but stress impact, determined by events and responses to them, has not been studied systematically. For the Salient Stressor Impact Questionnaire (SSIQ), the impact of events was assumed to depend on their salience and chronicity and the impact of responses on their chronicity and intensity with greater…
Descriptors: Measures (Individuals), Validity, Factor Analysis, Anxiety
Pages: 1  |  ...  |  794  |  795  |  796  |  797  |  798  |  799  |  800  |  801  |  802  |  ...  |  1201