跳至主要内容

Simulation Program to Determine Sample Size and Power for a Multiple Logistic Regression Model with Unspecified Covariate Distributions

Read full paper at:
http://www.scirp.org/journal/PaperInformation.aspx?PaperID=52556#.VJtsmcCAM4

Binary logistic regression models are commonly used to assess the association between outcomes and covariates. Many covariates are inherently continuous, and have a variety of distributions, including those that are heavily skewed to the left or right. Existing theoretical formulas, criteria, and simulation programs cannot accurately estimate the sample size and power of non-standard distributions. Therefore, we have developed a simulation program that uses Monte Carlo methods to estimate the exact power of a binary logistic regression model. This power calculation can be used for distributions of any shape and covariates of any type (continuous, ordinal, and nominal), and can account for nonlinear relationships between covariates and outcomes. For illustrative purposes, this simulation program is applied to real data obtained from a study on the influence of smoking on 90-day outcomes after acute atherothrombotic stroke. Our program is applicable to all effect sizes and makes it possible to apply various statistical methods, logistic regression and related simulations such as Bayesian inference with some modifications.
Cite this paper
Kumagai, N. , Akazawa, K. , Kataoka, H. , Hatakeyama, Y. and Okuhara, Y. (2014) Simulation Program to Determine Sample Size and Power for a Multiple Logistic Regression Model with Unspecified Covariate Distributions. Health, 6, 2973-2998. doi: 10.4236/health.2014.621336. 
 

[1] Ottenbacher, K.J., Ottenbacher, H.R., Tooth, L. and Ostir, G.V. (2004) A Review of Two Journals Found That Articles Using Multivariable Logistic Regression Frequently Did Not Report Commonly Recommended Assumptions. Journal of Clinical Epidemiology, 57, 1147-1152.
http://dx.doi.org/10.1016/j.jclinepi.2003.05.003
[2] Brenner, H. and Blettner, M. (1997) Controlling for Continuous Confounders in Epidemiologic Research. Epidemiology, 8, 429-434.
http://dx.doi.org/10.1097/00001648-199707000-00014
[3] Andrici, J., Cox, M.R. and Eslick, G.D. (2013) Cigarette Smoking and the Risk of Barrett’s Esophagus. A Systematic Review and Meta-Analysis. Journal of Gastroenterology and Hepatology, 28, 1258-1273.
http://dx.doi.org/10.1111/jgh.12230
[4] Bergtold, J., Yeager, E. and Featherstone, A. (2011) Sample Size and Robustness of Inferences from Logistic Regression in the Presence of Nonlinearity and Multicollinearity. The Agricultural & Applied Economics Association’s 2011 AAEA & NAREA Joint Annual Meeting, Pittsburgh, Pennsylvania, 24-26 July 2011.
[5] Demidenko, E. (2007) Sample Size Determination for Logistic Regression Revisited. Statistics in Medicine, 26, 3385-3397.
http://dx.doi.org/10.1002/sim.2771
[6] Whittemore, A.S. (1981) Sample Size for Logistic Regression with Small Response Probability. Journal of the American Statistical Association, 76, 27-32.
http://dx.doi.org/10.1080/01621459.1981.10477597
[7] Hsieh, F.Y., Bloch, D.A. and Larsen, M.D. (1998) A Simple Method of Sample Size Calculation for Linear and Logistic Regression. Statistics in Medicine, 17, 1623-1634.
http://dx.doi.org/10.1002/(SICI)1097-0258(19980730)17:14<1623::AID-SIM871>3.0.CO;2-S
[8] Peduzzi, P., Concato, J., Kemper, E., Holford, T.R. and Feinstein, A.R. (1996) A Simulation Study of the Number of Events per Variable in Logistic Regression Analysis. Journal of Clinical Epidemiology, 49, 1373-1379.
http://dx.doi.org/10.1016/S0895-4356(96)00236-3
[9] Vittinghoff, E. and McCulloch, C.E. (2007) Relaxing the Rule of Ten Events per Variable in Logistic and Cox Regression. American Journal of Epidemiology, 165, 710-718.
http://dx.doi.org/10.1093/aje/kwk052
[10] SAS/STAT(R) 9.2 User’s Guide, Second Edition.
[11] Hosmer, D.W. and Lemeshow, S. (2000) Applied Logistic Regression. 2nd Edition, John Wiley & Sons, New York.
http://dx.doi.org/10.1002/0471722146
[12] Messerli, F.H. and Panjrath, G.S. (2009) The J-Curve between Blood Pressure and Coronary Artery Disease or Essential Hypertension: Exactly How Essential? Journal of the American College of Cardiology, 54, 1827-1834.
http://dx.doi.org/10.1016/j.jacc.2009.05.073
[13] Kumagai, N., Okuhara, Y., Iiyama, T., Fujimoto, Y., Takekawa, H., Origasa, H., Kawanishi, Y. and Yamaguchi, T. (2013) Effects of Smoking on Outcomes after Acute Atherothrombotic Stroke in Japanese Men. Journal of the Neurological Sciences, 335, 164-1168.
http://dx.doi.org/10.1016/j.jns.2013.09.023
[14] Hsieh, F.Y. (1989) Sample Size Tables for Logistic Regression. Statistics in Medicine, 8, 795-802.
http://dx.doi.org/10.1002/sim.4780080704
[15] Fan, X., Felsovalyi, A., Sivo, S.A. and Keenan, S.C. (2003) SAS® for Monte Carlo Studies: A Guide for Quantitative Researchers. SAS Institute, Cary.
[16] Webb, M.C., Wilson, J.R. and Chong, J. (2004) An Analysis of Quasi-Complete Binary Data with Logistic Models: Applications to Alcohol Abuse Data. Journal of Data Science, 2, 273-285.
[17] Arnold, B.F., Hogan, D.R., Colford Jr., J.M. and Hubbard, A.E. (2011) Simulation Methods to Estimate Design Power: An Overview for Applied Research. BMC Medical Research Methodology, 11, 94.
http://dx.doi.org/10.1186/1471-2288-11-94
[18] Royston, P. and Sauerbrei, W. (2005) Building Multivariable Regression Models with Continuous Covariates in Clinical Epidemiology—With an Emphasis on Fractional Polynomials. Methods of Information in Medicine, 44, 561-571.
[19] Grund, B. and Sabin, C. (2010) Analysis of Biomarker Data: Logs, Odds Ratios, and Receiver Operating Characteristic Curves. Current Opinion in HIV & AIDS, 5, 473-479.
http://dx.doi.org/10.1097/COH.0b013e32833ed742
[20] Li, A. (2013) Handbook of SAS® DATA Step Programming. Chapman and Hall & CRC, London.                                               eww141225lx
[21] Burlew, M.M. (2007) SAS Macro Programming Made Easy. SAS Institute, Cary.
标签：

评论

发表评论

此博客中的热门博文

Does Immigration Promote the Investment of the Monopolistic Firm?

In the present paper, we examine the effect of increasing uncertainty of immigrants’ growth on the optimal timing of investment of a firm that has a monopolistic power over the labor market. It is revealed that when the uncertainty of immigrants’ growth is more than a threshold level, increasing uncertainty of immigrants’ growth accelerates the optimal timing of firms’ investment and enhances the economic growth, even if the uncertainty of immigrants’ growth is formulated by the geometric Brownian motion, which is in sharp contrast to the standard result that an increase in the uncertainty postpones the optimal timing. With an increase in the immigrants over the past ten years, workforces in the host countries have been growing significantly to the extent that the immigrants represent 70% of the increase in the workforce in Europe, and 47% in the United States as OECD indicates. In the present paper, we attempted to investigate the effect of increased uncertainty caused by the growi...
发表评论
阅读全文

Education Policy Implementation: A Mechanism for Enhancing Primary Education Development in Zanzibar

Education is one of the fundamental rights of individuals; therefore, the government of a country needs to develop and strengthen educational policy and quality as well as to ensure that everyone has equal access to basic education. The improvement of access and quality of education in the world is becoming as an essential factor in development, whereas the basic education (primary school), is acknowledged as a foundation of the higher educational development for every country. To fulfill this goal, governments introduce several policies and procedures; however, it requires some reforms and participation from the politician, policymakers, and other stakeholders to re-examine educational policy so that it can lead to multiplication and betterment of the reforms. Educational reforms actually focus on accountability. A positive educational development and reform is very challenging and needs more effort and strategy on how to use and utilize the resources effectively as such it can achie...
发表评论
阅读全文