On fitting latent class models for binary data: The estimation of standard errors

Menezes, Lilian M. de

doi:10.1348/000711099159026

Cited by 24 publications

(13 citation statements)

References 12 publications

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“…For this reason, we reanalyzed the data using latent class analysis to check the robustness of our conclusion that three distinct clusters of firms were extant in our sample. Latent class analysis differs from cluster analysis in that it is estimated by maximum likelihood and the number of clusters is determined by goodness‐of‐fit criteria (de Menezes, ). Bootstrapped χ 2 difference tests indicated that three clusters fit the data better than two clusters (χ 2 = 52.8, p < .001) and that four clusters did not fit the data better than three clusters (χ 2 = 19.6, ns).…”

Section: Methodsmentioning

confidence: 99%

Antecedents and Outcomes of Diversity and Equality Management Systems: An Integrated Institutional Agency and Strategic Human Resource Management Approach

Konrad¹,

Yang

Maurer³

2015

Hum Resour Manage

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This study examines the development and impact of diversity and equality management systems (DEMS). A national sample of human resource managers from 155 Canadian firms responded to surveys about their firm's diversity and equality management (DEM) practices. Cluster analysis and latent class modeling identified three distinct approaches to DEM: classical disparity DEMS showing limited development of DEM‐related practices, institutional DEMS involving complex selection mechanisms and monitoring of employment statistics, and configurational DEMS linking diversity to business strategy. Hypothesis‐testing analyses indicated that both institutional and configurational DEMS were predicted by coverage by the Canadian employment equity program, federal contractor status, and the presence of a diversity expert on staff. Only configurational DEMS was predicted by inclusion of HRM in developing business strategy. Configurational DEMS positively predicted the employment of workers with disabilities and members of visible minority groups as well as ROA. These findings support the proposition based on strategic human resource management (SHRM) theory that DEM practices should be considered as bundles and that vertical linkage to strategy is important for DEM effectiveness. As such, SHRM theory explains how managers can structure strategic responses to institutional pressures that go beyond requirements to achieve strategic goals. © 2015 Wiley Periodicals, Inc.

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Section: Methodsmentioning

confidence: 99%

Antecedents and Outcomes of Diversity and Equality Management Systems: An Integrated Institutional Agency and Strategic Human Resource Management Approach

Konrad¹,

Yang

Maurer³

2015

Hum Resour Manage

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“…Results reported by de Menezes (1999) show that the asymptotic theory may provide a very poor approximation, even if the sample size is of the order of 1000. Nevertheless, the theoretical comparison of 2d versus 2d − 1 parameters is valid.…”

Section: Behavior Of the Log-likelihood For The 2-factor Copula Modelmentioning

confidence: 99%

Factor Copula Models for Item Response Data

Nikoloulopoulos

Joe

2013

Psychometrika

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university of east anglia Harry Joe university of british columbia Factor or conditional independence models based on copulas are proposed for multivariate discrete data such as item responses. The factor copula models have interpretations of latent maxima/minima (in comparison with latent means) and can lead to more probability in the joint upper or lower tail compared with factor models based on the discretized multivariate normal distribution (or multidimensional normal ogive model). Details on maximum likelihood estimation of parameters for the factor copula model are given, as well as analysis of the behavior of the log-likelihood. Our general methodology is illustrated with several item response data sets, and it is shown that there is a substantial improvement on existing models both conceptually and in fit to data.

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“…De Menezes [5] has shown that the standard error based on the asymptotic information matrix evaluated at the MLEs can be problematic when data are sparse. In our analysis with binary test outcome, compared to the bootstrap method, Louis’s formula for adjusting information matrix based estimates of standard errors performs reasonably well when n = 122.…”

Section: Simulation Studiesmentioning

confidence: 99%

A fast Monte Carlo expectation–maximization algorithm for estimation in latent class model analysis with an application to assess diagnostic accuracy for cervical neoplasia in women with atypical glandular cells

Kang

Carter

Darcy³

et al. 2013

Journal of Applied Statistics

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In this article we use a latent class model (LCM) with prevalence modeled as a function of covariates to assess diagnostic test accuracy in situations where the true disease status is not observed, but observations on three or more conditionally independent diagnostic tests are available. A fast Monte Carlo EM (MCEM) algorithm with binary (disease) diagnostic data is implemented to estimate parameters of interest; namely, sensitivity, specificity, and prevalence of the disease as a function of covariates. To obtain standard errors for confidence interval construction of estimated parameters, the missing information principle is applied to adjust information matrix estimates. We compare the adjusted information matrix based standard error estimates with the bootstrap standard error estimates both obtained using the fast MCEM algorithm through an extensive Monte Carlo study. Simulation demonstrates that the adjusted information matrix approach estimates the standard error similarly with the bootstrap methods under certain scenarios. The bootstrap percentile intervals have satisfactory coverage probabilities. We then apply the LCM analysis to a real data set of 122 subjects from a Gynecologic Oncology Group (GOG) study of significant cervical lesion (S-CL) diagnosis in women with atypical glandular cells of undetermined significance (AGC) to compare the diagnostic accuracy of a histology-based evaluation, a CA-IX biomarker-based test and a human papillomavirus (HPV) DNA test.

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On fitting latent class models for binary data: The estimation of standard errors

Cited by 24 publications

References 12 publications

Antecedents and Outcomes of Diversity and Equality Management Systems: An Integrated Institutional Agency and Strategic Human Resource Management Approach

Antecedents and Outcomes of Diversity and Equality Management Systems: An Integrated Institutional Agency and Strategic Human Resource Management Approach

Factor Copula Models for Item Response Data

A fast Monte Carlo expectation–maximization algorithm for estimation in latent class model analysis with an application to assess diagnostic accuracy for cervical neoplasia in women with atypical glandular cells

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