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Estimation of optimum sample size allocation: an illustration with body mass index for evaluating the effect of a dietetic supplement. (English) Zbl 1434.62015

Summary: In many medical researches, it is needed to determine the optimal sample size allocation in a heterogeneous population. This paper proposes the algorithm for optimal sample size allocation. We consider the optimal allocation problem as an optimization problem and the solution is obtained by using Bisection, Secant, Regula-Falsi and other numerical methods. The performance of the algorithm for different numerical methods are analyzed and evaluated in terms of computing time, number of iterations and gain in accuracy using stratification. The efficacy of algorithm is evaluated for the response in terms of body mass index (BMI) to the dietetic supplement with diabetes mellitus, HIV/AIDS and cancer post-operatory recovery patients.

MSC:

62D05 Sampling theory, sample surveys
62P10 Applications of statistics to biology and medical sciences; meta analysis
Full Text: DOI

References:

[1] Bays, H. E., Chapman, R. H. and Grandy, S., The relationship of body mass index to diabetes mellitus, hypertension and dyslipidaemia: Comparison of data from two national surveys, Int. J. Clin. Practice61(5) (2007) 737-747.
[2] Berinde, V., Iterative Approximation of Fixed Points (Springer, Berlin, 2007). · Zbl 1165.47047
[3] Burgard, J. and Münnich, R., Modelling over and undercounts for design-based Monte Carlo studies in small area estimation: An application to the German register assisted census, Comput. Stat. Data Anal.56(10) (2012) 2856-2863. · Zbl 1255.62023
[4] Gabler, S., Ganninger, M. and Münnich, R., Optimal allocation of the sample size to strata under box constraints, Metrika75(2) (2012) 151-161. · Zbl 1238.62007
[5] Greenlee, H., Unger, J. M., LeBlanc, M., Ramsey, S. and Hershman, D. L., Association between body mass index and cancer survival in a pooled analysis of 22 clinical trials, Cancer Epidem. Biomar. Prev.26(1) (2017) 21-29.
[6] H. Hohnhold, Variants of optimal allocation in stratified sampling, Technical Report, Statistisches Bundesamt Wiesbaden (2009).
[7] Koethe, J. R., Bryan, C. A. Jenkins, Shepherd, E., Stinnette, S. E. and Sterling, T. R., An optimal body mass index range associated with improved immune reconstitution among HIV-infected adults initiating antiretroviral therapy, Clin. Infect. Dis.53(9) (2011) 952-960.
[8] Münnich, R., Sachs, E. W. and Wagner, M., Calibration of estimator-weights via semismooth Newton method, J. Global Optim.52(3) (2011) 471-485. · Zbl 1243.62010
[9] Münnich, R., Sachs, E. W. and Wagner, M., Numerical solution of optimal allocation problems in stratified sampling under box constraints, Adv. Stat. Anal.96(13) (2012) 435-450. · Zbl 1443.62024
[10] Neyman, J., On the two different aspects of the representative method: The method of stratified sampling and the method of purposive selection, J. Roy. Stat. Soc.97(4) (1934) 558-606. · JFM 61.1310.02
[11] Nocedal, J. and Wright, S., Numerical Optimization, 2nd edn., (Springer Nature, 2006). · Zbl 1104.65059
[12] Singh, S., Advanced Sampling Theory with Applications: How Michael Selected Amy (Kluwer Academic Publishers, 2003). · Zbl 1145.62304
[13] Stefanov, S., Minimization of a convex linear-fractional separable function subject to a convex inequality constraint or linear inequality constraint and bounds on the variables, Appl. Math. Res. Express2006(4) (2006) 1-24. · Zbl 1201.90159
[14] Stenger, H. and Gabler, S., Combining random sampling and census strategies. Justification of inclusion probabilities equal to 1, Metrika61(2) (2005) 137-156. · Zbl 1079.62013
[15] Temple, N. J., The marketing of dietary supplements: A Canadian perspective, Curr. Nutr. Rep.2(4) (2013) 167-173.
[16] Tschuprov, A. A., On the mathematical expectation of the moments of frequency distributions in the case of correlated observations, Metron2(3) (1923) 461-493.
[17] Vishwakarma, G. K. and Singh, H. P., An optimum allocation with a family of estimators using auxiliary information in sample surveys, J. Mod. Appl. Stat. Methods7(2) (2008) 478-487.
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