scholarly journals Fitting ACE structural equation models to case-control family data

2009 ◽  
pp. n/a-n/a ◽  
Author(s):  
K. N. Javaras ◽  
J. I. Hudson ◽  
N. M. Laird
Keyword(s):  
Structural Equation ◽  
Structural Equation Models ◽  
Case Control ◽  
Family Data ◽  
Control Family

Genetic analysis of age-at-onset traits based on case-control family data

2010 ◽  
Vol 29 (30) ◽  
pp. 3258-3266 ◽  
Author(s):  
Benjamin H. Yip ◽  
Tron Anders Moger ◽  
Yudi Pawitan
Keyword(s):  
Genetic Analysis ◽  
Age At Onset ◽  
Case Control ◽  
Family Data ◽  
Control Family

Incorporation of the time aspect into the liability-threshold model for case-control-family data

2017 ◽  
Author(s):  
Luise Cederkvist ◽  
Klaus K. Holst ◽  
Klaus K. Andersen ◽  
David V. Glidden ◽  
Kirsten Frederiksen ◽  
...  
Keyword(s):  
Threshold Model ◽  
Case Control ◽  
Family Data ◽  
Control Family

Family-Specific Approaches to the Analysis of Case-Control Family Data

Biometrics ◽  
2005 ◽  
Vol 62 (2) ◽  
pp. 488-494 ◽  
Author(s):  
J. M. Neuhaus ◽  
A. J. Scott ◽  
C. J. Wild
Keyword(s):  
Case Control ◽  
Family Data ◽  
Control Family

scholarly journals Missing genetic information in case-control family data with general semi-parametric shared frailty model

2010 ◽  
Vol 17 (2) ◽  
pp. 175-194 ◽  
Author(s):  
Anna Graber-Naidich ◽  
Malka Gorfine ◽  
Kathleen E. Malone ◽  
Li Hsu
Keyword(s):  
Genetic Information ◽  
Frailty Model ◽  
Case Control ◽  
Family Data ◽  
Shared Frailty Model ◽  
Shared Frailty ◽  
Control Family

Measuring the Big Five in Self-Report and Other Ratings

2000 ◽  
Vol 16 (1) ◽  
pp. 31-43 ◽  
Author(s):  
Claudio Barbaranelli ◽  
Gian Vittorio Caprara
Keyword(s):  
Big Five ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Error Variance ◽  
The Self ◽  
Self Report ◽  
Sources Of Information ◽  
Third Person ◽  
Fit Indexes ◽  
Response Modes

Summary: The aim of the study is to assess the construct validity of two different measures of the Big Five, matching two “response modes” (phrase-questionnaire and list of adjectives) and two sources of information or raters (self-report and other ratings). Two-hundred subjects, equally divided in males and females, were administered the self-report versions of the Big Five Questionnaire (BFQ) and the Big Five Observer (BFO), a list of bipolar pairs of adjectives ( Caprara, Barbaranelli, & Borgogni, 1993 , 1994 ). Every subject was rated by six acquaintances, then aggregated by means of the same instruments used for the self-report, but worded in a third-person format. The multitrait-multimethod matrix derived from these measures was then analyzed via Structural Equation Models according to the criteria proposed by Widaman (1985) , Marsh (1989) , and Bagozzi (1994) . In particular, four different models were compared. While the global fit indexes of the models were only moderate, convergent and discriminant validities were clearly supported, and method and error variance were moderate or low.

Collective Efficacy and Organizational Commitment in an Italian City Hall

2009 ◽  
Vol 14 (4) ◽  
pp. 363-371 ◽  
Author(s):  
Laura Borgogni ◽  
Silvia Dello Russo ◽  
Laura Petitta ◽  
Gary P. Latham
Keyword(s):  
Organizational Commitment ◽  
Collective Efficacy ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Practical Significance ◽  
City Hall ◽  
Italian City ◽  
Public Sector Managers ◽  
The Individual ◽  
Level Group

Employees (N = 170) of a City Hall in Italy were administered a questionnaire measuring collective efficacy (CE), perceptions of context (PoC), and organizational commitment (OC). Two facets of collective efficacy were identified, namely group and organizational. Structural equation models revealed that perceptions of top management display a stronger relationship with organizational collective efficacy, whereas employees’ perceptions of their colleagues and their direct superior are related to collective efficacy at the group level. Group collective efficacy had a stronger relationship with affective organizational commitment than did organizational collective efficacy. The theoretical significance of this study is in showing that CE is two-dimensional rather than unidimensional. The practical significance of this finding is that the PoC model provides a framework that public sector managers can use to increase the efficacy of the organization as a whole as well as the individual groups that compose it.

A Cautionary Note on Incremental Fit Indices Reported by LISREL

Methodology ◽  
2005 ◽  
Vol 1 (2) ◽  
pp. 81-85 ◽  
Author(s):  
Stefan C. Schmukle ◽  
Jochen Hardt
Keyword(s):  
Factor Analysis ◽  
Maximum Likelihood ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Null Model ◽  
Likelihood Estimation ◽  
Parameter Estimates ◽  
Fit Indices ◽  
Cautionary Note ◽  
Confirmatory Factor

Abstract. Incremental fit indices (IFIs) are regularly used when assessing the fit of structural equation models. IFIs are based on the comparison of the fit of a target model with that of a null model. For maximum-likelihood estimation, IFIs are usually computed by using the χ2 statistics of the maximum-likelihood fitting function (ML-χ2). However, LISREL recently changed the computation of IFIs. Since version 8.52, IFIs reported by LISREL are based on the χ2 statistics of the reweighted least squares fitting function (RLS-χ2). Although both functions lead to the same maximum-likelihood parameter estimates, the two χ2 statistics reach different values. Because these differences are especially large for null models, IFIs are affected in particular. Consequently, RLS-χ2 based IFIs in combination with conventional cut-off values explored for ML-χ2 based IFIs may lead to a wrong acceptance of models. We demonstrate this point by a confirmatory factor analysis in a sample of 2449 subjects.

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