Books and Articles

Acemoglu, D. and Pischke, J-S. (1999). Beyond Becker: Training in imperfect labour markets, The Economic Journal, 109(453): 112–142.
Alaska Airlines (2013). Alaska Airlines GE Flight Quest data mining challenge 2013, http://www.gequest.com/c/flight.
Allison, P.D. (2012). Handling Missing Data by Maximum Likelihood. Paper 312-2012, Proceedings of the SAS Global Forum 2012 Conference, Cary, NC: SAS Institute.
Anderberg, M. R. (1973). Cluster Analysis for Applications. New York: Academic Press.
Astrazeneca.com. (2014). Key Facts. URL: http://www.astrazeneca.com/About-Us/Key-facts, last accessed 4th Dec 2014.
Barker, N.A. A Practical Introduction to the Bootstrap Using the SAS System. SAS Working Paper PK02, www.SAS.com.
Bartone, P.T., Eid, J., Johnsen, B.H., Laberg, J.C. and Snook SA. (2009). Big five personality factors, hardiness, and social judgment as predictors of leader performance, Leadership & Organization Development Journal, 30(6): 498-521.
Bauer, H.H., and Hammerschmidt, M. (2005). Customer-based corporate valuation: Integrating the Concepts of Customer Equity and Shareholder Value, Management Decision, 43(3): 331-348.
Becker G.S. (1975). Human Capital: A Theoretical and Empirical Analysis, With Special Reference to Education. New York: National Bureau of Economic Research.
Belsley, D.A., Kuh, E., and Welsch, R.E. (1980). Regression Diagnostics: Identifying Influential Data and Sources of Collinearity. New York: John Wiley & Sons, Inc.
Berengueres, J., & Efimov, D. (2014). Airline new customer tier level forecasting for real-time resource allocation of a miles program. Journal of Big Data, 1(1), 1-13.
Boom, A. (2005). Firms' investments in general training and the skilled labour market, Labour Economics, 12(6): 781–805.
Brown, RG., Meyer, RF. & D'esopo, DA. 1961. The fundamental theorem of exponential smoothing. Operations Research, 9(5): 673-685.
Bunnage, M. E. (2011). Getting pharmaceutical R&D back on target. Nature Chemical Biology, 7(6): 335-339.
Cascio, W. and Boudreau, J. W. (2008), Investing in People: Financial Impact of Human Resource Initiatives, Pearson Education, Inc, Upper Saddle River, New Jersey.
Cascio, W.F. (1991) Costing Human Resources: The Financial Impact of Behavior in Organizations (3rd ed.), Boston: Kent.
Cody, R.P. and Smith J.K. (1997). Applied Statistics and the SAS® Programming Language (4th ed), Upper Saddle River, NJ: Prentice-Hall.
Cohen, J., Cohen, P., West, S.G. and Aiken, L.S. (2003). Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences (3rd ed.) Mahwah, NJ: Lawrence Erlbaum.
Collins R., Peto R., & Armitage J. (2002). Oxford Clinical Trials Service Unit, International Journal of Clinical Practice, 56(1): 53-56.
Costello, A. B., & Osborne, J. W. (2005). Best practices in exploratory factor analysis: four recommendations for getting the most from your analysis, Practical Assessment, Research & Evaluation, 10(7): 1-9.
Davenport, T.H. & Dyché, J. (2013). Big Data in Big Companies. SAS Institute / International Institute of Analytics.
Davison, A. C. & D. V. Hinkley. (1997). Bootstrap Methods and their Application. Cambridge: Cambridge University Press.
Delwiche, L. D. & Slaughter, S. J. (2012). The Little SAS® Book: A Primer (5th ed.).
Cary, NC: SAS Institute.
DiMasi, J.A., Hansen, R.W., & Grabowski, H.G. (2003). The price of innovation: new estimates of drug development costs, Journal of Health Economics, 22(2): 151–185.
Dong, Y., & Peng, C. Y. J. (2013). Principled missing data methods for researchers. SpringerPlus, 2(1): 1-17.
Dull, T. (2014). A Non-Geek’s Big Data Playbook: Hadoop and the Enterprise Data Warehouse. SAS Best Practices White Paper. Cary, NC: SAS Institute.
Efron, B. & R. J. Tibshirani. (1993). An Introduction to the Bootstrap. New York: Chapman & Hall.
Enders, C. K. (2005). An SAS Macro for implementing the modified Bollen-Stine bootstrap for missing data: Implementing the bootstrap using existing structural equation modeling software, Structural Equation Modeling, 12(4): 620-641.
Fabrigar, L. R., Wegener, D. T., MacCallum, R. C., & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research, Psychological Methods, 4(3): 272-299.
Fleiss, J. L., Levin, B., and Paik, M. C. (2003), Statistical Methods for Rates and Proportions, 3rd Edition, Hoboken, NJ: John Wiley & Sons.
FrieslandCampina ‘About Us’ website. (2010). http://www.frieslandcampina.com/english/about-us.aspx. Last accessed 17th May 2010.
Gaskin, C.J. and Happell, B. (2014). On exploratory factor analysis: A review of recent evidence, an assessment of current practice, and recommendations for future use, International Journal of Nursing Studies, 51(3): 511–521.
Gerbing, D. W., & Anderson, J. C. (1987). Improper solutions in the analysis of covariance structures: Their interpretability and a comparison of alternate respecifications, Psychometrika, 52(1--March): 99-111.
Goldberg, R. J. (1997, September). PROC FACTOR: how to interpret the output of a real-world example. Proceedings of the Twenty-Second Annual SAS Users Group International Conference, Paper 269. Cary, NC: SAS Institute.
Grabowski, H.G. (2002). Patents and new product development in the pharmaceutical and biotechnology industries, Science and Cents: Exploring the Economics of Biotechnology, 87–104.
Graham, J. W., & Hofer, S. M. (2000). Multiple imputation in multivariate research. In T. D. Little, K. U. Schnabel, & J. Baumert, (Eds.), Modeling Longitudinal And Multilevel Data: Practical Issues, Applied Approaches, and Specific Examples. (181-186). Mahwah, NJ: Lawrence Erlbaum.
Graham, J. W., Cumsille, P. E., & Elek-Fisk, E. (2003). Methods for handling missing data. In J. A. Schinka & W. F. Velicer (Eds.). Research Methods in Psychology (pp. 87-114). Volume 2 of Handbook of Psychology (I. B. Weiner, Editor-in-Chief). New York: John Wiley & Sons.
Greasley, A. (2004). Simulation Modelling for Business. Ashgate Publishing, Aldershot, UK.
Hair Jr, J.F., Anderson, R.E., Tatham, R.L., Black W.C. (1998). Multivariate Data Analysis (5th Ed). Prentice-Hall: Upper Saddle River, New Jersey.
Hall, P. (1992). The Bootstrap and Edgeworth Expansion. New York: Springer-Verlag.
Hancock, G.R. and Mueller, R.O. (eds.). (2013). Structural Equation Modeling: A Second Course (2nd Ed.), Charlotte, NC: Information Age Publishing.
Harman, H. H. (1976). Modern Factor Analysis (3rd Ed. Revised) Chicago: University of Chicago Press.
Harris, C. W. and Kaiser, H. F. (1964). Oblique factor analytic solutions by orthogonal transformations, Psychometrika, 29(4):347-362.
Hebbar, P. (2012). Off the Beaten Path: Create Unusual Graphs with GTL. Proceedings of the SAS Global Forum 2012 Conference, Cary, NC: SAS Institute, Paper 267-2012.
Herper, M. (2013). The cost of creating a new drug now $5 billion, pushing big pharma to change, Forbes, 8/11/2013. http://www.forbes.com/sites/matthewherper/2013/08/11/how-the-staggering-cost-of-inventing-new-drugs-is-shaping-the-future-of-medicine/.
Holt, CC. 1957. Forecasting Seasonals and Trends by Exponentially Weighted Moving Averages, Pittsburgh, PA: Carnegie Institute of Technology.
Hom, P.W. and Griffeth, R.W. (1994). Employee Turnover. Cincinnati: OH. South-Western College Publishing.
IDC. (2014). Data Growth, Business Opportunities, and the IT Imperatives. http://www.emc.com/leadership/digital-universe/2014iview/executive-summary.htm. Last accessed 1st April 2015.
Jackofsky, E. F. (1984). Turnover and job performance: An integrated process model, Academy of Management Review, 9(1): 74-83.
Jung, S. (2013). Exploratory factor analysis with small sample sizes: A comparison of three approaches, Behavioural Processes, 97: 90–95.
Kendall, M. G. and Stuart, A. (1979), The Advanced Theory of Statistics, volume 2, Inference and Relationship, New York: Macmillan.
Kitagawa, G. 2010. Introduction to Time Series Modeling. Boca Raton: Chapman & Hall/CRC.
Kline, R.B. (2010). Principles and Practice of Structural Equation Modeling (3rd Ed.) NY: Guilford Press.
Kuhfeld, W. (2010). Statistical Graphics in SAS: An Introduction to the Graph Template Language and the Statistical Graphics Procedures. Cary, NC: SAS Institute.
Lawrence, R.D., Hong, S.J. & Cherrier, J. (2003). Passenger-based predictive modeling of airline no-show rates. Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining. pp. 397-406.
Lee, G.J. (2010). Employee flow as an integrated and qualitative system: Impact on business-to-business service quality, Journal of Business-to-Business Marketing, 17(1): 1-28.
Lehrer, J. (2010). The truth wears off: Is there something wrong with the scientific method?, The New Yorker Annals of Science, December 13.
Liou, J.J.H. & Tzeng, G-H. (2010). A dominance-based rough set approach to customer behavior in the airline market. Information Sciences, 180(11): 2230-2238.
Little, R. J. A., & Rubin, D. B. (2002). Statistical Analysis with Missing Data (2nd ed.). Hoboken, NJ: John Wiley & Sons.
Little, T.D., Cunningham, W.A., Shahar, G. and Widaman, K.F. (2002). To parcel or not to parcel: Exploring the question, weighing the merits, Structural Equation Modeling, 9(2): 151-173.
Lockwood, C. M., & MacKinnon, D. P. (1998). Bootstrapping the standard error of the mediated effect. Proceedings of the Twenty-Third annual SAS Users Group International Conference, Paper 180 (pp. 997-1002). Cary, NC: SAS Institute. (available from SAS website)
Loehlin, J.C. (1992). Latent Variable Models : An Introduction to Factor, Path, and Structural Analysis (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates.
MacCallum, R. C., Widaman, K. F., Zhang, S. B., & Hong, S. H. (1999). Sample size in factor analysis, Psychological Methods, 4(1): 84-99.
Malthouse E.C. & Blattberg R.C. (2005). Can we predict customer lifetime value?, Journal of Interactive Marketing, 19(1): 2-16.
Matange, S. & Heath, D. (2011). Statistical Graphics Procedures by Example: Effective Graphs Using SAS®. Cary, NC: SAS Institute.
Muenchen, R. A. (2015). The popularity of data analysis software. URL: http://r4stats.com/articles/popularity. Last accessed 16th Sept 2015.
Mpofu, B. (2010). South Africa: Lack of skills hinders mining sector growth, Business Day, Wednesday, 3rd March.
Opperman, E.R. (2012). The economic value of high performance work systems: An Oracle case study. University of the Witwatersrand MBA Thesis.
Pammolli, F., Magazzini, L., & Riccaboni, M. (2011). The productivity crisis in pharmaceutical R&D, Nature Reviews Drug Discovery, 10(6): 428-438.
Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1988). SERVQUAL : A Multiple-Item Scale for Measuring Consumer Perceptions of Service Quality, Journal of Retailing, 64(1): 12-37.
Paul, S. M., Mytelka, D. S., Dunwiddie, C. T., Persinger, C. C., Munos, B. H., Lindborg, S. R., & Schacht, A. L. (2010). How to improve R&D productivity: the pharmaceutical industry's grand challenge, Nature Reviews Drug Discovery, 9(3): 203-214.
Pfeuffer, C. (2015). Job Skills That Lead to Bigger Paychecks. http://career-advice.monster.com/salary-benefits/salary-information/best-paid-job-skills/article.aspx.
Pollitt, D. (2007). Software solves problem of global succession planning at Friesland Foods: System Supports Careers and Development of International High-Flyers, Human Resource Management International Digest, 15(6): 21-23.
Prado, R. & West, M. 2010. Time Series Modeling, Computation, and Inference. Boca Raton: Chapman & Hall/CRC.
Preacher, K.J. and Hayes, A.F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models, Behavior Research Methods, Instruments, & Computers, 36 (4): 717-731
Rubin, D.B. (1987). Multiple Imputation for Nonresponse in Surveys. New York: Wiley.
RxList.com (2014). Crestor. URL: http://www.rxlist.com/crestor-drug/clinical-pharmacology.htm, last accessed 3rd Dec 2014.
Santos, J.R.A. (1998). PROC FACTOR: A tool for extracting hidden gems from a mountain of variables. Proceedings of the Twenty-Third Annual SAS Users Group International Conference, Paper 240. Cary, NC: SAS Institute.
Scannell, J. W., Blanckley, A., Boldon, H., & Warrington, B. (2012). Diagnosing the decline in pharmaceutical R&D efficiency, Nature Reviews Drug Discovery, 11(3): 191-200.
Schafer, J. L. (1997). Analysis of Incomplete Multivariate Data. London: Chapman & Hall.
Schafer. J. L. & Graham, J. W. (2002). Missing data: Our view of the state of the art, Psychological Methods, 7(2): 147-177.
Shao, J. and Tu, D. (1995). The Jackknife and Bootstrap. New York: Springer-Verlag.
Stacey, A.G. (2005). The reliability and validity of the item means and standard deviations of ordinal level response data, Management Dynamics, 14(3): 2-25.
Stacey, A.G. (2006). Estimating the means and standard deviations of rank ordered survey items, Management Dynamics, 15(3): 26-35.
Stevenson, W.J. & Ozgur, C. 2006. Introduction to Management Science with Spreadsheets. Boston: McGraw-Hill.
Stine, R. (1989). An introduction to bootstrap methods: Examples and ideas, Sociological Methods & Research, 18: 243–291.
Suhr, D.D. Exploratory or confirmatory factor analysis? Proceedings of the Thirty-first Annual SAS Users Group International Conference (SUGI) 31 Paper 200-31, Cary, NC: SAS Institute.
Taylor, Y. (2013). Patent breadth versus length: An examination of the pharmaceutical industry. Duke University Job Market Working Paper, http://sites.duke.edu/ytaylor/files/2013/11/PatentBvL.pdf
The Skills Portal. (2008). Mining industry skills: Another R9 billion needed for artisan training. http://www.skillsportal.co.za/content/another-r9-billion-needed-artisan-training. Last accessed 18th May 2010.
Turban, E. & Meredith, J.R. 1994. Fundamentals of management science. 6th edition. Burr Ridge, Illinois: Irwin.
United State Military Academy at West Point website, About West Point. (2010) http://www.usma.edu/about.asp. Last accessed 21st May 2010.
Vorhies, B. (2013). How Many “V”s in Big Data – The Characteristics that Define Big Data. Data-Magnum Business Foundation Series #2. URL: http://data-magnum.com/how-many-vs-in-big-data-the-characteristics-that-define-big-data/
Wayman, J. C. (2003). Multiple Imputation For Missing Data: What Is It And How Can I Use It? Paper presented at the Annual Meeting of the American Educational Research Association, Chicago.
Wheelwright, SC. & Makridakis, S. 1985. Forecasting Methods for Management. 4th edition. New York: John Wiley & Sons.
Wicklin, R. (2013). Simulating Data with SAS. SAS Institute. Cary, NC.
Winters, PR. 1960. Forecasting sales by exponentially weighted moving averages, Management Science, 6(3): 324-342.
Wothke, W. (1993). Nonpositive definite matrices in structural modeling. In K. A. Bollen & J. S. Long (Eds.), Testing Structural Equation Models (pp. 256-93). Newbury Park, CA: Sage.
Last updated: April 18, 2017
..................Content has been hidden....................

You can't read the all page of ebook, please click here login for view all page.
Reset
3.138.35.193