#### Filter Results:

- Full text PDF available (24)

#### Publication Year

1985

2016

#### Publication Type

#### Co-author

#### Publication Venue

#### Key Phrases

Learn More

Although the literature on alternatives to effect indicators is growing, there has been little attention given to evaluating causal and composite (formative) indicators. This paper provides an overview of this topic by contrasting ways of assessing the validity of effect and causal indicators in structural equation models (SEMs). It also draws a distinction… (More)

A controversial area in covariance structure models is the assessment of overall model fit. Researchers have expressed concern over the influence of sample size on measures of fit. Many contradictory claims have been made regarding which fit statistics are affected by N. Part of the confusion is due to there being two types of sample size effects that are… (More)

- Kenneth A Bollen, Shawn Bauldry
- Psychological methods
- 2011

In the last 2 decades attention to causal (and formative) indicators has grown. Accompanying this growth has been the belief that one can classify indicators into 2 categories: effect (reflective) indicators and causal (formative) indicators. We argue that the dichotomous view is too simple. Instead, there are effect indicators and 3 types of variables on… (More)

- Kenneth A. Bollen
- MIS Quarterly
- 2011

- Patrick J Curran, Kenneth A Bollen, Pamela Paxton, James Kirby, Feinian Chen
- Multivariate behavioral research
- 2002

The noncentral chi-square distribution plays a key role in structural equation modeling (SEM). The likelihood ratio test statistic that accompanies virtually all SEMs asymptotically follows a noncentral chi-square under certain assumptions relating to misspecification and multivariate distribution. Many scholars use the noncentral chi-square distribution in… (More)

Causality was at the center of the early history of structural equation models (SEMs) which continue to serve as the most popular approach to causal analysis in the social sciences. Through decades of development, critics and defenses of the capability of SEMs to support causal inference have accumulated. A variety of misunderstandings and myths about the… (More)

- Kenneth A Bollen
- Psychological methods
- 2007

R. D. Howell, E. Breivik, and J. B. Wilcox (2007) have argued that causal (formative) indicators are inherently subject to interpretational confounding. That is, they have argued that using causal (formative) indicators leads the empirical meaning of a latent variable to be other than that assigned to it by a researcher. Their critique of causal (formative)… (More)

- K A Bollen, K F Ting
- Psychological methods
- 2000

The authors propose a confirmatory tetrad analysis test to distinguish causal from effect indicators in structural equation models. The test uses "nested" vanishing tetrads that are often implied when comparing causal and effect indicator models. The authors present typical models that researchers can use to determine the vanishing tetrads for 4 or more… (More)

Using democracy in empirical work requires accurate measurement. Yet, most policy and academic research presupposes the accuracy of available measures. This article explores judge-specific measurement errors in cross-national indicators of liberal democracy. The authors evaluate the magnitude of these errors in widely used measures of democracy and… (More)

A "tetrad" refers to the difference in the products of certain covariances (or correlations) among four random variables. A structural equation model often implies that some tetrads should be zero. These "vanishing tetrads" provide a means to test structural equation models. In this paper we develop confirmatory tetrad analysis (C T A). C T A applies a… (More)