Interpretational confounding is due to misspecification, not to type of indicator: comment on Howell, Breivik, and Wilcox (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) indicators rests on several claims: (a) A latent variable exists apart from the model when there are effect (reflective) indicators but not when there are causal (formative) indicators, (b) causal (formative) indicators need not have the same consequences, (c) causal (formative) indicators are inherently subject to interpretational confounding, and (d) a researcher cannot detect interpretational confounding when using causal (formative) indicators. This article shows that each claim is false. Rather, interpretational confounding is more a problem of structural misspecification of a model combined with an underidentified model that leaves these misspecifications undetected. Interpretational confounding does not occur if the model is correctly specified whether a researcher has causal (formative) or effect (reflective) indicators. It is the validity of a model not the type of indicator that determines the potential for interpretational confounding.     

The Alignment of Measures and Constructs in Organizational Research: The Case of Testing Measurement Models of Creativity

Purpose  

Organizational creativity research has a curious misalignment between construct definitions and measurement model specifications—definitions embrace multiple facets, but empirical measures do not. The purpose of this study was to examine potential measurement model misspecification in organizational creativity research. We compare whether creativity is best assessed as a unidimensional common latent construct model with reflective indicators or as a multi-dimensional composite latent construct model with formative indicators.     

制造行业管理胜任力与绩效关系的实证研究

通过对571名制造型企业管理者的问卷调查,探索并验证了制造业管理胜任力结构维度,检验了不同背景因素对管理胜任力的影响。结果表明:制造业管理胜任力具有六维结构,包含22个指标,其信度和效度较好;不同管理层次的管理者在制造过程控制和市场营销策划维度上的评价有显著性差异,不同企业规模下的管理者在行业核心理念和产品系统管理维度上的评价有显著性差异;产品系统管理与市场营销策划能力对制造业管理者绩效有良好的预测力。同时发现,制造业管理胜任力不能较好地解释周边绩效的变异量。     

Violent crime and its relation to subjective social stress indicators: The case of Israel

Although the effects of objective social stressors on violent crime have been studied extensively, the effects of subjective perception of stress factors have been neglected in criminological research. The present study investigates the relationship between the subjective perception of external stress factors and homicide and robbery rates, within a stress model according to which the probability of violence as a reaction to stress will increase when social support systems fail or malfunction. In the present context, subjective perception of social stress is conceived as expressions of worry or dissatisfaction regarding cardinal life domains such as the economic, security, or political situation. Support systems are defined here in terms of national solidarity, which is expressed as positive (or improved) attitudes regarding the relations between various segments of the population. The data regarding the subjective indicators were derived from continuing surveys of representative samples of urban Israeli population during the years 1967–1985. Fourteen stress indicators and two solidarity indicators were included. The periods covered range from less than 4 years to more than 16 years. The theoretical model was generally supported by the findings: both homicide and robbery were found to be related to most of the stress indicators as predicted. The two solidarity indicators were in line with the model in respect of robbery but not homicide. The consistency of the findings with the model is particularly noteworthy in view of the great variation among the independent variables regarding the number of observations and periods of time covered. Some theoretical implications of the findings are discussed, and suggestions are made for future research.     

Integrating covariates into circumplex structures: an extension procedure for Browne’s circular stochastic process model

Circumplex structures are elements of various psychological domains. Most work focuses on assessing the circular ordering of circumplex indicators and their relationships with covariates. In this article, an extension procedure for Browne’s circumplex model is presented. Our approach models the relationships among circumplex indicators and the relationships of covariates with a latent circumplex simultaneously without affecting the circumplex indicators’ positions on the circumplex. The approach builds upon Browne’s Fourier series parameterization of a correlation function, which is used to model the latent circumplex correlation structure. It extends the shape of the correlation function to the profile of each covariate’s correlations with the circumplex. The model is specified in the framework of structural equation modeling, thereby making it possible to test various hypotheses. Procedures are presented for deriving interval estimates for the parameters that relate the covariates to the circumplex. The model is compared to other approaches for assessing the relationships of a circumplex with covariates. The results of the exemplary applications and a simulation study were in favor of the suggested model. The approach is furthermore illustrated with a real-data example, focusing on the relationships between the interpersonal circumplex and the rivalry and admiration aspects of narcissism.     

Exploring the Relationship Between Gender,Mental Health Needs,and Treatment Orders in a Metropolitan Juvenile Court

We explored personal, social, and legal factors associated with different types of mental health treatment orders in one Missouri metropolitan court where the majority of system-involved youth are African-American. The research question under investigation is: with objective assessment information at their disposal, do judges order mental health treatment based on indicators of need or do they follow the pattern found in other studies where demographic and legal variables are key indicators? The bivariate results indicate that while males and females do not differ in mental health status, they do differ in psychosocial needs and offense patterns. In the multivariate analysis, the mental health treatment specific model indicates that commonly used indicators of need, prior mental health status and being female are related to receiving treatment orders. In the substance abuse treatment specific model, the significant factors are closely aligned with need: drug offenses, substance abuse problems, and negative influence of peers.     

Determination of Weights for Health Related Quality of Life Indicators among Kidney Patients: A Fuzzy Decision Making Method

Health-Related Quality of Life (HRQoL) is one of the significant current discussions in the health fraternity. It encompasses multidimensional indicators and serves the purpose of evaluating health quality among patients. Patients’ perceptions of the impact of disease and treatment and the indicators such as physical, psychological, social function and well being are normally investigated. However there is no clear suggestion of which indicators contributed more than others. The arbitrary nature of HRQoL paves the way for fuzzy theory in evaluation of indicators. This paper describes the application of a fuzzy decision making method in ranking indicators of HRQoL among kidney patients. Four experts in health fraternity were selected as decision makers to elicit information regarding health related status of chronic kidney disease patients over eight HRQoL indicators. The decision makers were required to rate the regularity of experiencing health-related problems in linguistic judgment among the patients. The five linguistics variables were used as input data to a modified version of Fuzzy Simple Additive Weight decision making model. The modified six-step method was possible to tap the extent of decision makers’ opinions on the severity of HRQoL experienced by the patients. It is shown that the indicator of role-physical recorded the lowest problematic level while the indicator of mental health recorded the highest problematic level experienced by the patients. The ranking signifies the impact of the indicators to health quality specifically the chronic kidney disease patients.     

The Nature and Dynamics of Post-Sterilization Regret in Married Women 1

Data for nine different indicators of regret were collected from 213 married women with a tubal sterilization and 137 wives of men with a vasectomy at 1,2, and 3 years following surgical sterilization. Relationships between the indicators across the 3 years and within each year were analyzed, using two psychological models. A final, combined model was synthesized and fitted to the data. This model addresses many of the important issues of reliability and validity that have plagued the literature on post-sterilization regret for years.     

Suicide and attempted suicide: their relation to subjective social stress indicators

We investigated the relationship between the subjective perception of external stress and suicidal behavior, using a stress model which indicated that the probability of suicide and attempted suicide, as a reaction to stress, increases when social support systems fail or malfunction. We conceived the subjective perception of social stress as expressions of worry or dissatisfaction regarding cardinal life domains such as economic, security, or political situations. We defined support systems in terms of national solidarity expressed as positive (or improved) attitudes regarding the relations between various segments of the population, and we derived the data regarding the subjective indicators from continuing surveys of representative samples of urban Israeli population during the years 1967 through 1979. Eight stress indicators and three solidarity indicators were included, and our findings generally supported the theoretical model. However, the findings regarding men conformed best in relation to suicide, whereas those regarding women confirmed the theoretical model mainly in relation to attempted suicide. Contrary to the model, female suicide rates decreased in times of stress. Feelings of social solidarity in the population were found to reduce suicidal behavior of both men and women.     

The problem of measurement model misspecification in behavioral and organizational research and some recommended solutions

The purpose of this study was to review the distinction between formative- and reflective-indicator measurement models, articulate a set of criteria for deciding whether measures are formative or reflective, illustrate some commonly researched constructs that have formative indicators, empirically test the effects of measurement model misspecification using a Monte Carlo simulation, and recommend new scale development procedures for latent constructs with formative indicators. Results of the Monte Carlo simulation indicated that measurement model misspecification can inflate unstandardized structural parameter estimates by as much as 400% or deflate them by as much as 80% and lead to Type I or Type II errors of inference, depending on whether the exogenous or the endogenous latent construct is misspecified. Implications of this research are discussed.     

Psychological Foundations of Financial Planning for Retirement

Little is known about the psychological mechanisms that underlie financial planning for retirement. Most studies of financial planning and investing have used demographic indicators (e.g., age, gender, income) to predict individual differences in saving. In the present study, a model of planning is tested in which psychological indicators (future time perspective, retirement goal clarity, and self-rated financial knowledge) are posited to mediate the relationship between demographic indicators and saving behaviors. Path-analytic techniques were used to test the model, based on data from 265 middle-aged working adults. Analyses revealed substantial support for the role of psychological factors in the retirement planning process. Findings have theoretical implications for the development of psychologically based models of planning, as well as applied implications for those who seek to understand the psychomotivational forces that underlie tendencies to plan and save.     

The Job Demand-Control-Social Support Model and Wellness/Health Outcomes: A European Study

The EUROTEACH study which is reported here, comprised 2796 secondary school teachers from 13 European countries. The study firstly aimed at testing an extended Job Demand-Control-Social support (JDCS) model and checking its gender specificity. While this study failed to provide evidence for the buffer hypothesis derived from the JDCS-model, the strain hypothesis was mostly supported. Additional job conditions tested in this study proved to be important predictors of the outcome variables (emotional exhaustion, depersonalisation, personal accomplishment, somatic complaints and job satisfaction) and standard of living indicators also added explained variance in these outcomes. The study proved that the JDCS model cannot be called a male model. Secondly the study looked at the comparability of 3 European regions (South, West, East). Apart from important regional differences in job conditions, standard of living indicators and outcomes, the most important finding is that the JDCS model explains most variance in outcome variables in Western Europe, and the least in Eastern Europe, and thus seems to suffer from a Western bias.     

A tetrad test for causal indicators

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 variables. They also provide the vanishing tetrads for mixtures of causal and effect indicators, for models with fewer than 4 indicators per latent variable, or for cases with correlated errors. The authors illustrate the test results for several simulation and empirical examples and emphasize that their technique is a theory-testing rather than a model-generating approach. They also review limitations of the procedure including the indistinguishable tetrad equivalent models, the largely unknown finite sample behavior of the test statistic, and the inability of any procedure to fully validate a model specification.     

结构方程建模中的题目打包策略

结构方程建模中题目打包法的优缺点包括：指标数据质量变好、模型拟合程度提高; 估计偏差不大, 可校正; 估计稳定, 但降低了敏感性与可证伪性。打包法的前提条件是单维、同质, 适合结构模型分析, 不适合测量模型分析。对于单维测验, 给出了一个打包流程。对于通常的多个子量表(多维结构)测验, 推荐在子量表内打包, 每个子量表打包成1个指标或者3个指标, 用于结构方程建模。     

Truth and beauty in scientific reason

A rationalist and realist model of scientific revolutions will be constructed by reference to two categories of criteria of theory-evaluation, denominated indicators of truth and of beauty. Whereas indicators of truth are formulateda priori and thus unite science in the pursuit of verisimilitude, aesthetic criteria are inductive constructs which lag behind the progression of theories in truthlikeness. Revolutions occur when the evaluative divergence between the two categories of criteria proves too wide to be recomposed or overlooked. This model of revolutions depends upon a substantial new treatment of aesthetic criteria in science with which much of the paper will therefore be occupied.     

Some effects of positive life events on community mental health

Measures of positive and negative events were derived from a life-event inventory to test the predictions of an equilibrium model and a positive mental health model of psychological well-being. These measures were related to indicators of individual and community well-being with data obtained through a household survey of 454 residents. Residents who reported more negative events also reported more psychological distress and less positive adjustment. Positive events were associated with reports of positive adjustment. An analysis of census tract scores on life events revealed that the relative absence of positive events in census tracts was associated with higher service utilization rates to the community mental health center serving those tracts. The number of negative events was unrelated to service rates for census tracts but was related to several demographic indicators of well-being.     

Higher Order Structure of Personality and Mental Health: Does General Affectivity Matter?

The higher order personality model, namely the Big Two, was tested in 2 studies (Ns = 878 and 467, respectively) by controlling for the effects of both general affectivity and common method variance. Study 2 also examined the associations of the metatraits with different mental health indicators through regression analyses. The results consistently provided support for the validity of the Big Two model in the latent space, with and without the effects of general affectivity and the common method variance. Moreover, in both studies, the high correlation between stability and plasticity decreased when these 2 method effects were controlled statistically. The regression analyses also showed that the associations of plasticity and stability with the indicators of both subjective and psychological well-being, as well as psychopathology, were consistent with the theoretical arguments behind the Big Two.     

Quantifying definitional relations in psychological measurement

Quantitative inferences about psychological attributes, such as extraversion, depression and empathy, involve measurement instruments as well as mathematical models that specify how indicators should be aggregated. The type of model that is appropriate for doing so is conditional on the type of relation that exists between an attribute, its facets and its indicators. The common assumption is that such relations are causal relations. Here, instead, we address definitional attribute-facet relations. Our aim is to find an appropriate mathematical model for when an attribute is defined in terms of facets, instead of causing or being caused by facets. In doing so, we describe the semantics of definitions in logical form. From this form we then derive continuous functions for attribute-facet relations using fuzzy logic. A model with main effects and interactions between facets seems to be more powerful for representing definitional relations than traditional formative and reflective models. This has important implications for measurement in basic and applied research.     

Building an identifiable latent class model with covariate effects on underlying and measured variables

In recent years, latent class models have proven useful for analyzing relationships between measured multiple indicators and covariates of interest. Such models summarize shared features of the multiple indicators as an underlying categorical variable, and the indicators' substantive associations with predictors are built directly and indirectly in unique model parameters. In this paper, we provide a detailed study on the theory and application of building models that allow mediated relationships between primary predictors and latent class membership, but that also allow direct effects of secondary covariates on the indicators themselves. Theory for model identification is developed. We detail an Expectation-Maximization algorithm for parameter estimation, standard error calculation, and convergent properties. Comparison of the proposed model with models underlying existing latent class modeling software is provided. A detailed analysis of how visual impairments affect older persons' functioning requiring distance vision is used for illustration.This work was supported by National Institute on Aging (NIA) Program Project P01-AG-10184-03 and National Institutes of Mental Health grant R01-MH-56639-01A1. Dr. Bandeen-Roche is a Brookdale National Fellow. The authors wish to thank Drs. Gary Rubin and Sheila West for kindly making the Salisbury Eye Evaluation data available. We also thank the Editor, the Associate Editor, and three referees for their valuable comments.     

The Impact of Item Misspecification and Dichotomization on Class and Parameter Recovery in LCA of Count Data

Mixture analysis of count data has become increasingly popular among researchers of substance use, behavioral analysis, and program evaluation. However, this increase in popularity seems to have occurred along with adoption of some conventions in model specification based on arbitrary heuristics that may impact the validity of results. Findings from a systematic review of recent drug and alcohol publications suggested count variables are often dichotomized or misspecified as continuous normal indicators in mixture analysis. Prior research suggests that misspecifying skewed distributions of continuous indicators in mixture analysis introduces bias, though the consequences of this practice when applied to count indicators has not been studied. The present work describes results from a simulation study examining bias in mixture recovery when count indicators are dichotomized (median split; presence vs. absence), ordinalized, or the distribution is misspecified (continuous normal; incorrect count distribution). All distributional misspecifications and methods of categorizing resulted in greater bias in parameter estimates and recovery of class membership relative to specifying the true distribution, though dichotomization appeared to improve class enumeration accuracy relative to all other specifications. Overall, results demonstrate the importance of accurately modeling count indicators in mixture analysis, as misspecification and categorizing data can distort study outcomes.