Development of uncertainty-based work injury model using Bayesian structural equation modelling

References

• Bellamy, L.J., Geyer, T.A.W., & Wilkinson, J. (2008). Development of a functional model which integrates human factors, safety management systems and wider organisational issues. Safety Science, 46(3), 461–492.
   Web of Science ®Google Scholar
• Bennett, J.D., & Passmore, D.L. (1985). Multinomial logit analysis of injury severity in US underground bituminous coal mines, 1975–1982. Accident Analysis and Prevention, 17(5), 399–408.
   PubMed Web of Science ®Google Scholar
• Berger, J.O. (1985). Statistical decision theory and Bayesian analysis (2nd ed.). New York, NY: Springer-Verlag.
   Google Scholar
• Bernardo, J.M., & Smith, A.F.M. (1994). Bayesian theory. New York, NY: Wiley.
   Google Scholar
• Bhattacherjee, A. (1991). Mine safety management: An application of risk analysis, forecasting techniques, and Markov process to injury experience data (Ph.D. thesis). Pennsylvania State University, University Park, PA.
   Google Scholar
• Bhattacherjee, A., Mukherjee, N., Misra, R.B., Ghosh, A., & Maiti J. (1997). Design of safety system for jamadoba group of collieries: A consultancy project report (Report No. 1). Kharagpur: Department of Mining Engineering and Electrical Engineering, Indian Institute of Technology.
   Google Scholar
• Bollen, K.A., & Stine, R.A. (1993). Bootstrapping goodness-of-fit measures in structural equation models. In K.A. Bollen, & J. Long (Eds.), Testing structural equation models (pp.111–135). Newbury Park, CA: Sage.
   Google Scholar
• Brogmus, G.E. (2007). Day of the week lost time occupational injury trends in the US by gender and industry and their implications for work scheduling. Ergonomics, 50(3), 446–474.
   PubMed Web of Science ®Google Scholar
• Browne, M.W. (1984). Asymptotically distribution-free methods for the analysis of covariance structures. British Journal of Mathematical and Statistical Psychology, 37, 62–83.
   PubMed Web of Science ®Google Scholar
• Carayon, P. (2006). Human factors of complex sociotechnical systems. Applied Ergonomics, 37(4), 525–535.
   PubMed Web of Science ®Google Scholar
• Cheyne, A., Oliver, A., Tomás, J.M., & Cox, S. (2002). The architecture of employee attitudes to safety in the manufacturing sector. Personnel Review, 31(5–6), 649–670.
   Web of Science ®Google Scholar
• Coleman, P.J., & Kerkering, J.C. (2007). Measuring mining safety with injury statistics: Lost workdays as indicators of risk. Journal of Safety Research, 38, 523–533.
   PubMed Web of Science ®Google Scholar
• Cox, S., Jones, B., & Rycraft, H. (2004). Behavioural approaches to safety management within UK reactor plants. Safety Science, 42, 825–839.
   Web of Science ®Google Scholar
• Dunson, D.B., Chen, Z., & Harry, J. (2003). A Bayesian approach for joint modeling of cluster size and subunit-specific outcomes. Biometrics, 59(3), 521–530.
   PubMed Web of Science ®Google Scholar
• Gelfand, A.E., & Smith, A.F.M. (1990). Sampling-based approaches to calculate marginal densities. Journal of the American Statistical Association, 85, 398–409.
   Web of Science ®Google Scholar
• Geman, S., & Geman D. (1984). Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 6, 721–741.
   PubMed Web of Science ®Google Scholar
• Ghosh, A.K., Bhattacherjee, A., & Chau, N. (2004). Relationships of working conditions and individual characteristics to occupational injuries: A case-control study in coal miners. Journal of Occupational Health, 46, 470–478.
   PubMed Web of Science ®Google Scholar
• Ghosh, A.K., Bhattacherjee, A., & Ray, S.C. (1998). An application of system dynamics in the mine safety studies. Mineral Resource Engineering, 7, 131–147.
   Google Scholar
• Groves, W.A., Kecojevic, V.J., & Komljenovic, D. (2007). Analysis of fatalities and injuries involving mining equipment. Journal of Safety Research, 38, 461–470.
   PubMed Web of Science ®Google Scholar
• Härmä, M. (2006). Work hours in relation to work stress, recovery and health. Scandinavian Journal of Work, Environment and Health, 32(6), 502–514.
   PubMed Web of Science ®Google Scholar
• Harrell, W.A. (1990). Perceived risk of occupational injury: Control over pace of work and blue-collar versus white-collar work. Perceptual Motor Skills, 70, 1351–1359.
   PubMed Web of Science ®Google Scholar
• Hu, L.T., & Bentler, P.M. (1995). Evaluation model fit. In R.H. Hoyle (Ed.), Structural equation modeling: Concepts, issues, and applications (pp. 76–99). Thousand Oaks, CA: Sage.
   Google Scholar
• Hu, L.T., Bentler, P.M., & Kano, Y. (1992). Can test statistics in covariance structure analysis be trusted? Psychological Bulletin, 112, 351–362.
   PubMed Web of Science ®Google Scholar
• Jansen, J.C., & Brent, A.C. (2005). Reducing accidents in the mining industry – an integrated approach. Journal of South African Institute of Mining and Metallurgy, 105, 719–725.
   Web of Science ®Google Scholar
• Joreskog, K.G., & Soerbom, D. (1994). PRELIS: A preprocessor for LISREL. Chicago, IL: Scientific Software International.
   Google Scholar
• Karra, V.K. (2005). Analysis of non-fatal and fatal injury rates for mine operator and contractor employees and the influence of work location. Journal of Safety Research, 36, 413–421.
   PubMed Web of Science ®Google Scholar
• Kass, R.E., & Raftery, A.E. (1995). Bayes factors. Journal of the American Statistical Association, 90, 773–795.
   Web of Science ®Google Scholar
• Kecojevic, V., Komljenovic, D., Groves, W., & Radomsky, M. (2007). An analysis of equipment-related fatal accidents in US mining operations: 1995–2005. Safety Science, 45, 864–874.
   Web of Science ®Google Scholar
• Khanzode, V.V., Maiti, J., & Ray, P.K. (2010). Occupational injury and accident research: A comprehensive review. Safety Science, 50(5), 1355–1367.
   Web of Science ®Google Scholar
• Khanzode, V.V., Maiti, J., Ray, P.K., & Tewari, V.K. (2010). Injury severity assessment for underground coalmine workers. Applied Ergonomics, 41(2), 242–250.
   PubMed Web of Science ®Google Scholar
• Komljenovic, D., Groves, W.A., & Kecojevic, V.J. (2008). Injuries in US mining operations – a preliminary risk analysis. Safety Science, 46, 792–801.
   Web of Science ®Google Scholar
• Lee, S.-Y. (2007). Structural equation modeling: A Bayesian approach (Wiley series in probability and statistics). New York, NY: Wiley.
   Google Scholar
• Li, X., Song, X., & Meng, X. (2009). Fatal gas accident prevention in coal mine: A perspective from management feedback complexity. Procedia Earth and Planetary Science, 1(1), 1673–1677.
   Google Scholar
• Maiti, J. (1999). An investigation of multivariate statistical models to evaluate mine safety performance (Unpublished Ph.D. thesis). Department of Mining Engineering, Indian Institute of Technology, Kharagpur.
   Google Scholar
• Maiti, J., & Bhattacherjee, A. (1999). Evaluation of risk of occupational injuries among underground coal mine workers through multinomial logit analysis. Journal of Safety Research, 30, 93–101.
   Web of Science ®Google Scholar
• Maiti, J., Bhattacherjee, A., Gupta, U.C., & Roy, S.C. (1999). An application of logit model to coal mine injury experience data. Mineral Resource Engineering, 8(2), 239–253.
   Google Scholar
• Maiti, J., Chatterjee, S., & Bangdiwala, S.I. (2004). Determinants of work injuries in mines – an application of structural equation modeling. Injury Control and Safety Promotion, 11(1), 29–37.
   PubMedGoogle Scholar
• Maruyama, G., & McGarvey, B. (1980). Evaluating causal models: An application of maximum likelihood analysis of structural equations. Psychological Bulletin, 87(3), 502–512.
   Web of Science ®Google Scholar
• Muthén, B.O. (1993). Goodness of fit with categorical and other non-normal variables. In K.A. Bollen, & J. Long (Eds.), Testing structural equation models (pp. 205–234). Newbury Park, CA: Sage.
   Google Scholar
• Muthén, B.O. (2010). Bayesian analysis in Mplus: A brief introduction. Retrieved from http://www.statmodel.com
   Google Scholar
• NIOSH Report. (2011). The economic burden of occupational fatal injuries to civilian workers in the United States based on the census of fatal occupational injuries, 1992–2002 (Publication number 2011-130). Washington, DC: DHHS (NIOSH).
   Google Scholar
• Onder, S. (2013). Evaluation of occupational injuries with lost days among opencast coal mine workers through logistic regression models. Safety Science, 59, 86–92.
   Web of Science ®Google Scholar
• Onder, M., & Adiguzel, E. (2010). Evaluation of occupational fatalities among underground coal mine workers through hierarchical loglinear models. Industrial Health, 48, 872–878.
   PubMed Web of Science ®Google Scholar
• Palei, S.K., & Das, S.K. (2009). Logistic regression model for prediction of roof fall risks in bord and pillar workings in coal mines: An approach. Safety Science, 47(1), 88–96.
   Web of Science ®Google Scholar
• Palomo, J., Dunson, D., & Bollen, K. (2007). Bayesian structural equation modeling. In S. Lee (Ed.), Handbook of latent variable and related models (pp. 163–188). Amsterdam: North Holland.
   Google Scholar
• Paul, P.S., & Maiti, J. (2007). The role of behaviour factors on safety management in underground mines. Safety Science, 45, 449–471.
   Web of Science ®Google Scholar
• Paul, P.S., Maiti, J., Dasgupta, S., & Forjuoh, S.N. (2005). An epidemiological study of injury in mines: implications for safety promotion. International Journal of Injury Control and Safety Promotion, 12(3), 157–165.
   PubMedGoogle Scholar
• Peele, P.B., & Tollerud, D.J. (2005). Depression and occupational injury: Results of a pilot investigation. Journal of Occupational and Environmental Medicine, 47(4), 424–427.
   PubMed Web of Science ®Google Scholar
• Phiri, J. (1989). Development of statistical indices for the evaluation of hazards in Longwall face operations (Ph.D. thesis). Pennsylvania State University, University Park, PA.
   Google Scholar
• Proctor, S.P., White, R.F., Robins, T.G., Echeverria, D., & Rocskay, A.Z. (1996). Effect of overtime work on cognitive function in automotive workers. Scandinavian Journal of Work, Environment and Health, 22(2), 124–132.
   PubMed Web of Science ®Google Scholar
• Raediker, B., Janssen, D., Schomann, C., & Nachreiner, F. (2006). Extended working hours and health. Chronobiology International, 23(6), 1305–1316.
   PubMed Web of Science ®Google Scholar
• Raftery, A., & Lewis, S. (1992). How many iterations in the Gibbs sampler. Bayesian Statistics, 4(2), 763–773.
   Google Scholar
• Sari, M., Selcuk, A.S., Karpuz, C., & Duzgun, H.S.B. (2009). Stochastic modeling of accident risks associated with an underground coal mine in Turkey. Safety Science, 47, 78–87.
   Web of Science ®Google Scholar
• Shaw, B.E., Sanders, M.S., & Peay, J. (1989, August 14–16). Research to determine the contribution of system factors including human error in the occurrence of underground injury accidents. Proceedings XVI Training Resources Applied to Mining, Pennsylvania State University, University Park, PA.
   Google Scholar
• Sherry, P. (1991). Person-environment fit and accident prediction. Journal of Business and Psychology, 5, 411–416.
   Google Scholar
• Skrondal, A., & Rabe-Hesketh, S. (2004). Generalized latent variable modeling: Multilevel, longitudinal, and structural equation models. Boca Raton, FL: Chapman & Hall/CRC.
   Google Scholar
• Vegso, S., Cantley, L., Slade, M., Taiwo, O., Sircar, K., Rabinowitz, P., … Cullen, M.R. (2007). Extended work hours and risk of acute occupational injury: A case-crossover study of workers in manufacturing. American Journal of Industrial Medicine, 50(8), 597–603.
   PubMed Web of Science ®Google Scholar
• Warnes, G.R. (2005). mcgibbsit: Warnes and Raftery's MCGibbsit MCMC diagnostic (R package version 1.0.5). Retrieved from http://cran.r-project.org/web/packages/mcgibbsit/mcgibbsit.pdf
   Google Scholar