Patrick Mair

Formative Constructs Implemented via Common Factors

Recently there has been a renewed interest in formative measurement and its role in properly specified models. Formative measurement models are difficult to identify, and hence to estimate and test. Existing solutions to the identification problem are shown to not adequately represent the formative constructs of interest. We propose a new two-step approach to operationalize a formatively measured construct that allows a closely matched common factor equivalent to be included in any structural equation model. We provide an artificial example and an original empirical study of privacy to illustrate our approach. Detailed proofs are given in an appendix.

Making friends and communicating on Facebook: Implications for the access to social capital

Abstract In this paper, we explore the dynamics of access to social capital on Facebook. Existing approaches to network-based social capital measures are adapted to the case of Facebook and applied to the friendship and communication data of 438,851 users. These measures are correlated to user data in order to identify advantageous behavior for optimizing the possible access to social capital. We find that the access to social capital on Facebook is primarily based on a reasonable amount of active communication. Exaggerated friending and posting behavior can deteriorate the access to social capital. Furthermore, we investigate which kinds of posts are most advantageous as well as questions of homophily based on social capital.

What Carries a Mediation Process? Configural Analysis of Mediation

Mediation is a process that links a predictor and a criterion via a mediator variable. Mediation can be full or partial. This well-established definition operates at the level of variables even if they are categorical. In this article, two new approaches to the analysis of mediation are proposed. Both of these approaches focus on the analysis of categorical variables. The first involves mediation analysis at the level of configurations instead of variables. Thus, mediation can be incorporated into the arsenal of methods of analysis for person-oriented research. Second, it is proposed that Configural Frequency Analysis (CFA) can be used for both exploration and confirmation of mediation relationships among categorical variables. The implications of using CFA are first that mediation hypotheses can be tested at the level of individual configurations instead of variables. Second, this approach leaves the door open for different types of mediation processes to exist within the same set. Using a data example, it is illustrated that aggregate-level analysis can overlook mediation processes that operate at the level of individual configurations.

Generating Nonnormal Multivariate Data Using Copulas: Applications to SEM.

This article develops a procedure based on copulas to simulate multivariate nonnormal data that satisfy a prespecified variance-covariance matrix. The covariance matrix used can comply with a specific moment structure form (e.g., a factor analysis or a general structural equation model). Thus, the method is particularly useful for Monte Carlo evaluation of structural equation models within the context of nonnormal data. The new procedure for nonnormal data simulation is theoretically described and also implemented in the widely used R environment. The quality of the method is assessed by Monte Carlo simulations. A 1-sample test on the observed covariance matrix based on the copula methodology is proposed. This new test for evaluating the quality of a simulation is defined through a particular structural model specification and is robust against normality violations.

EQS Goes R: Simulations for SEM Using the Package REQS

The REQS package is an interface between the R environment of statistical computing and the EQS software for structural equation modeling. The package consists of 3 main functions that read EQS script files and import the results into R, call EQS script files from R, and run EQS script files from R and import the results after EQS computations. The components a user needs are R and EQS. We give a short introduction to R and EQS, elaborate the functionalities of the package, and show how to use the package by means of several examples with special emphasis on simulations. The first simulation investigates the effects of nonnormal data on various test statistics. The second simulation conducts a power analysis for a path coefficient in a 2-group model.

Application scenarios for nonstandard log-linear models.

In this article, the authors have 2 aims. First, hierarchical, nonhierarchical, and nonstandard log-linear models are defined. Second, application scenarios are presented for nonhierarchical and nonstandard models, with illustrations of where these scenarios can occur. Parameters can be interpreted in regard to their formal meaning and in regard to their magnitude. The interpretation of the meaning of parameters is the main focus of this article. Design matrices are used to describe the hypotheses tested in models and to illustrate cases in which parameters are interpretable. Also, design matrices are used to show where and how nonstandard models differ from standard hierarchical models. Coding schemes are discussed, in particular, dummy coding and effects coding. Data examples are given with data and models discussed in the literature.

Motivation, values, and work design as drivers of participation in the R open source project for statistical computing

Significance Over the last years, the open-source environment R has become the most popular environment for statistical computing and data analysis across many fields of research. The developer community is highly active: Thousands of packages are available in the official Comprehensive R Archive Network repository and more on developer platforms like GitHub or R-Forge. One question that has not been studied yet is as follows: why do people contribute to the R environment? What are the key motives that drive package authors? Do these developers have specific personal value structures? Are some work environments more conducive to productivity than others? This study is the first empirical study, to our knowledge, performed within the R package author community that finds answers to these questions. One of the cornerstones of the R system for statistical computing is the multitude of packages contributed by numerous package authors. This amount of packages makes an extremely broad range of statistical techniques and other quantitative methods freely available. Thus far, no empirical study has investigated psychological factors that drive authors to participate in the R project. This article presents a study of R package authors, collecting data on different types of participation (number of packages, participation in mailing lists, participation in conferences), three psychological scales (types of motivation, psychological values, and work design characteristics), and various socio-demographic factors. The data are analyzed using item response models and subsequent generalized linear models, showing that the most important determinants for participation are a hybrid form of motivation and the social characteristics of the work design. Other factors are found to have less impact or influence only specific aspects of participation.

Goodness-of-Fit Assessment in Multidimensional Scaling and Unfolding

ABSTRACT Judging goodness of fit in multidimensional scaling requires a comprehensive set of diagnostic tools instead of relying on stress rules of thumb. This article elaborates on corresponding strategies and gives practical guidelines for researchers to obtain a clear picture of the goodness of fit of a solution. Special emphasis will be placed on the use of permutation tests. The second part of the article focuses on goodness-of-fit assessment of an important variant of multidimensional scaling called unfolding, which can be applied to a broad range of psychological data settings. Two real-life data sets are presented in order to walk the reader through the entire set of diagnostic measures, tests, and plots. R code is provided as supplementary information that makes the whole goodness-of-fit assessment workflow, as presented in this article, fully reproducible.

A network perspective on comorbid depression in adolescents with obsessive-compulsive disorder

People with obsessive-compulsive disorder [OCD] frequently suffer from depression, a comorbidity associated with greater symptom severity and suicide risk. We examined the associations between OCD and depression symptoms in 87 adolescents with primary OCD. We computed an association network, a graphical LASSO, and a directed acyclic graph (DAG) to model symptom interactions. Models showed OCD and depression as separate syndromes linked by bridge symptoms. Bridges between the two disorders emerged between obsessional problems in the OCD syndrome, and guilt, concentration problems, and sadness in the depression syndrome. A directed network indicated that OCD symptoms directionally precede depression symptoms. Concentration impairment emerged as a highly central node that may be distinctive to adolescents. We conclude that the network approach to mental disorders provides a new way to understand the etiology and maintenance of comorbid OCD-depression. Network analysis can improve research and treatment of mental disorder comorbidities by generating hypotheses concerning potential causal symptom structures and by identifying symptoms that may bridge disorders.

Analysis of Dwell Times in Web Usage Mining

In this contribution we focus on dwell times a user spends on various areas of a web site within a session. We assume that dwell times may be adequately modeled by a Weibull distribution which is a flexible and common approach in survival analysis. Furthermore we introduce heterogeneity by various parameterizations of dwell time densities by means of proportional hazards models. According to these assumptions the observed data stem from a mixture of Weibull densities. Estimation is based on EM-algorithm and model selection may be guided by BIC. Identification of mixture components corresponds to a segmentation of users/sessions. A real life data set stemming from the analysis of a world wide operating eCommerce application is provided. The corresponding computations are performed with the mixPHM package in R.