Results 1  10
of
12
Bayesian Estimation and Testing of Structural Equation Models
 Psychometrika
, 1999
"... The Gibbs sampler can be used to obtain samples of arbitrary size from the posterior distribution over the parameters of a structural equation model (SEM) given covariance data and a prior distribution over the parameters. Point estimates, standard deviations and interval estimates for the parameter ..."
Abstract

Cited by 27 (8 self)
 Add to MetaCart
The Gibbs sampler can be used to obtain samples of arbitrary size from the posterior distribution over the parameters of a structural equation model (SEM) given covariance data and a prior distribution over the parameters. Point estimates, standard deviations and interval estimates for the parameters can be computed from these samples. If the prior distribution over the parameters is uninformative, the posterior is proportional to the likelihood, and asymptotically the inferences based on the Gibbs sample are the same as those based on the maximum likelihood solution, e.g., output from LISREL or EQS. In small samples, however, the likelihood surface is not Gaussian and in some cases contains local maxima. Nevertheless, the Gibbs sample comes from the correct posterior distribution over the parameters regardless of the sample size and the shape of the likelihood surface. With an informative prior distribution over the parameters, the posterior can be used to make inferences about the parameters of underidentified models, as we illustrate on a simple errorsinvariables model.
Partial Least Squares: A critical review and a potential alternative
 Proceedings of the Administrative Sciences Association of Canada (ASAC ) Conference
, 2005
"... This paper provides a critique of the perceived advantages of PLS over covariancebased methods for estimating structural equation (SEM) models. Specific attention is drawn to the lack of consistency of PLS estimates. The two stage least squares method of estimation is described, proposed as a potent ..."
Abstract

Cited by 4 (0 self)
 Add to MetaCart
This paper provides a critique of the perceived advantages of PLS over covariancebased methods for estimating structural equation (SEM) models. Specific attention is drawn to the lack of consistency of PLS estimates. The two stage least squares method of estimation is described, proposed as a potential alternative, and compared with PLS in a simulation study.
Quasi Maximum Likelihood Estimation of Structural Equation Models With Multiple Interaction and Quadratic Effects
"... The development of statistically efficient and computationally practicable estimation methods for the analysis of structural equation models with multiple nonlinear effects has been called for by substantive researchers in psychology, marketing research, and sociology. But the development of efficie ..."
Abstract

Cited by 2 (0 self)
 Add to MetaCart
The development of statistically efficient and computationally practicable estimation methods for the analysis of structural equation models with multiple nonlinear effects has been called for by substantive researchers in psychology, marketing research, and sociology. But the development of efficient methods is complicated by the fact that a nonlinear model structure implies specifically nonnormal multivariate distributions for the indicator variables. In this paper, nonlinear structural equation models with quadratic forms are introduced and a new QuasiMaximum Likelihood method for simultaneous estimation of model parameters is developed with the focus on statistical efficiency and computational practicability. The QuasiML method is based on an approximation of the nonnormal density function of the joint indicator vector by a product of a normal and a conditionally normal density. The results of MonteCarlo studies for the new QuasiML method indicate that the parameter estimation is almost as efficient as ML estimation, whereas ML estimation is only computationally practical for elementary models. Also, the QuasiML method outperforms other currently available methods with respect to efficiency. It is demonstrated in a MonteCarlo study that the QuasiML method permits computationally feasible and very efficient analysis of models with multiple latent nonlinear effects. Finally, the applicability of the QuasiML method is illustrated by an empirical example of an aging study in psychology. Key words: structural equation modeling, quadratic form of normal variates, latent interaction effect, moderator effect, QuasiML estimation, variance function model. 1 1.
TwoStage Least Squares (2SLS) and Structural Equation Models (SEM). http://csusap.csu. edu.au./~eoczkows/home.htm Samuel Gebreselassie and E. Ludi (2007), Agricultural Commercialisation in Coffeegrowing Areas of Ethiopia. Paper presented at the
 Fifth International Conference on the Ethiopian
, 2003
"... These notes describe the 2SLS estimator for latent variable models developed by Bollen (1996). The technique separately estimates the measurement model and structural model of SEM. One can therefore use it either as a stand alone procedure for a full SEM or combine it with factor analysis, for examp ..."
Abstract

Cited by 2 (0 self)
 Add to MetaCart
These notes describe the 2SLS estimator for latent variable models developed by Bollen (1996). The technique separately estimates the measurement model and structural model of SEM. One can therefore use it either as a stand alone procedure for a full SEM or combine it with factor analysis, for example, establish the measurement model using factor analysis and then employ 2SLS for the structural model only. The advantages of using 2SLS over the more conventional maximum likelihood (ML) method for SEM include: • It does not require any distributional assumptions for RHS independent variables, they can be nonnormal, binary, etc. • In the context of a multiequation nonrecursive SEM it isolates specification errors to single equations, see Bollen (2001). • It is computationally simple and does not require the use of numerical optimisation algorithms. • It easily caters for nonlinear and interactions effects, see Bollen and Paxton (1998). • It permits the routine use of often ignored diagnostic testing procedures for problems such as heteroscedasticity and specification error, see Pesaran and Taylor (1999). • Simulation evidence from econometrics suggests that 2SLS may perform better in small samples than ML, see Bollen (1996, pp120121). There are however some disadvantages in using 2SLS compared to ML, these include: • The ML estimator is more efficient than 2SLS given its simultaneous estimation of all relationships, hence ML will dominate 2SLS always in sufficiently large samples if all assumptions are valid and the model specification is correct. Effectively ML is more efficient (if the model is valid) as it uses much more information than 2SLS. • Unlike the ML method, the 2SLS estimator depends upon the choice of reference variable. The implication being that different 2SLS estimates result given different scaling variables. • Programs with diagram facilities such as EQS do not exist for 2SLS. One needs to logically work through the structure of the model to specify individual equations for all the relationships for the 2SLS estimator.
Nonlinear Change Models in Populations with Unobserved Heterogeneity
"... Abstract. When unobserved heterogeneity exists in populations where the phenomenon of interest is governed by a functional form of change linear in its parameters, the growth mixture model (GMM) is useful for modeling change conditional on latent class. However, when the functional form of interest ..."
Abstract

Cited by 1 (0 self)
 Add to MetaCart
Abstract. When unobserved heterogeneity exists in populations where the phenomenon of interest is governed by a functional form of change linear in its parameters, the growth mixture model (GMM) is useful for modeling change conditional on latent class. However, when the functional form of interest is nonlinear in its parameters, the GMM is not very useful because it is based on a system of equations linear in its parameters. The nonlinear change mixture model (NCMM) is proposed, which explicitly addresses unobserved heterogeneity in situations where change follows a nonlinear functional form. Due to the integration of nonlinear multilevel models and finite mixture models, neither of which generally have closed form solutions, analytic solutions do not generally exist for the NCMM. Five methods of parameter estimation are developed and evaluated with a comprehensive Monte Carlo simulation study. The simulation showed that the parameters of the NCMM can be accurately estimated with several of the proposed methods, and that the method of choice depends on the precise question of interest.
ENCOURAGING BEST PRACTICE IN QUANTITATIVE MANAGEMENT RESEARCH: AN INCOMPLETE LIST OF OPPORTUNITIES *
"... The paper identifies some common problems encountered in quantitative methodology and provides information on current best practice to resolve these problems. We first discuss issues pertaining to variable measurement and concerns regarding the underlying relationships among variables. We then highl ..."
Abstract

Cited by 1 (0 self)
 Add to MetaCart
The paper identifies some common problems encountered in quantitative methodology and provides information on current best practice to resolve these problems. We first discuss issues pertaining to variable measurement and concerns regarding the underlying relationships among variables. We then highlight several advances in estimation methodology that may circumvent issues encountered in common practice. Finally, we discuss approaches that move beyond existing research designs, including the development and use of datasets that embody linkages across levels of analysis, or combine qualitative and quantitative methods. * All authors contributed equally, and are listed in reverse alphabetical order. We appreciate comments from Inigo Arroniz, Babu John Mariadoss, Glenn Hoetker, Sonali Shah, and Mike Wright. The usual disclaimer applies. 1 Social research comprises of two broad methods of logical reasoning: (a) deductive reasoning that involves the confirmation of hypotheses from theories, and (b) inductive reasoning that involves the development of generalizations from specific observations (Kerlinger 1972). For example, Christensen (2006) highlights the importance of both inductive and
The Effect of Structural Characteristics on Family Planning Program Performance in Cte d'Ivoire and Nigeria
"... include the prices that facilities may charge their clients as well as the training of providers and other qualityrelated measures of services. 2 Our interest in structure and performance comes at a time when there are numerous trends which involve major restructuring of the way health care servic ..."
Abstract
 Add to MetaCart
include the prices that facilities may charge their clients as well as the training of providers and other qualityrelated measures of services. 2 Our interest in structure and performance comes at a time when there are numerous trends which involve major restructuring of the way health care services are provided in developing countries. These include efforts to devolve services from the central administrative control to lower levels of command. Decentralization is a major undertaking and often involves complete restructuring of the management and logistics system within a country. In addition, the Cairo ICPD includes a call for creating and strengthening linkages between services, the underlying belief being that the linkage of the various services would increase their utilization. Integration at various levels has become an important policy target for many reproductive health programs. The debate also continues about the most appropriate form of service provision and what roles sho
Operating Authority and Quality in Family Planning Service Provision and Cost in Tanzania
"... This paper will focus on two aspects of service provision in Tanzania: the impact of family planning service quality and the impact of facility operating authority on service utilization and cost at the facility level. In mainland Tanzania, the government runs a comprehensive system of tiered facili ..."
Abstract
 Add to MetaCart
This paper will focus on two aspects of service provision in Tanzania: the impact of family planning service quality and the impact of facility operating authority on service utilization and cost at the facility level. In mainland Tanzania, the government runs a comprehensive system of tiered facilities, almost all of which offer some type of family planning service. In addition, government hospitals, health centers, and dispensaries have their private or nongovernmental organization (NGO) counterparts. The survey used in this analysis follows two of these NGOs, those that are affiliated with the International Planned Parenthood Federation (UMATI), and 2 those run by the NGO Marie Stopes. A series of authority, facility type, and interactive indicators measures facility level differences in provision, net of the effect of quality and the characteristics of the service environment. Since these are facility level differences unexplained by the family planning procedures or other facility characteristics, these are referred to as "management" effects. Quality, measured as an index score, captures such specifics as the exam procedures for new family planning clients, whether or not information, education, and communication (IEC) is standard practice, what type of staff typically performs the physical exam, and other substantive characteristics of the personal service given to each family planning client. An important outstanding question in the literature is whether quality or accessability is the most important. This would necessarily drive the investment decision toward either improving existing services or expanding coverage into new areas. At the facility level, however, it is difficult to measure access, since we only have information on users of the service, for wh...
POPULATIONS WHEN CLASS MEMBERSHIP IS UNKNOWN: DEFINING AND DEVELOPING THE LATENT CLASSIFICATION DIFFERENTIAL CHANGE MODEL
, 2005
"... by Kenneth Kelley III Standard methods for analyzing change generally assume that the population of interest is homogeneous or that heterogeneity is known. When a population consists of unknown subpopulations, the parameters within each of the latent classes may be unique to that particular class. I ..."
Abstract
 Add to MetaCart
by Kenneth Kelley III Standard methods for analyzing change generally assume that the population of interest is homogeneous or that heterogeneity is known. When a population consists of unknown subpopulations, the parameters within each of the latent classes may be unique to that particular class. In such a situation the results of standard techniques for analyzing change are misleading, because such methods ignore unobserved heterogeneity and treat the population as if it were homogeneous. The growth mixture model (GMM; Muthén, 2001a; Muthén, 2001b; Muthén, 2002) partly addresses the problem of unknown heterogeneity because the parameters of the GMM are conditional on latent class membership. However, the GMM is necessarily restricted to models of change linear in their parameters (such as polynomial change models). The latent classification
About the Authors
, 2002
"... The Faculty of Commerce Working Paper Series is intended to provide staff and students with a means of communicating new and evolving ideas in order to encourage academic debate. Working papers, as the title suggests, should not necessarily be taken as completed works or final expressions of opinion ..."
Abstract
 Add to MetaCart
The Faculty of Commerce Working Paper Series is intended to provide staff and students with a means of communicating new and evolving ideas in order to encourage academic debate. Working papers, as the title suggests, should not necessarily be taken as completed works or final expressions of opinions. All working papers are subject to review prior to publication by one or more editors or referees familiar with the discipline area. Normally, working papers may be freely quoted and/or reproduced provided proper reference to the author and source is given. When a working paper is published on a restricted basis,