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Journal articles on the topic 'Complex Survey Design'

Author: Grafiati

Published: 4 June 2021

Last updated: 14 February 2022

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1

Reiter, Jerome P., Elaine L. Zanutto, and Larry W. Hunter. "Analytical Modeling in Complex Surveys of Work Practices." ILR Review 59, no. 1 (2005): 82–100. http://dx.doi.org/10.1177/001979390505900105.

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Quantitative industrial relations research frequently relies on data collected from large surveys of establishments that use complex sampling designs, such as stratified and unequal probability sampling. The authors analyze two complex surveys of establishments, the National Organizations Survey and the National Survey of Establishments. They discuss design-based (survey-weighted) and model-based (unweighted) strategies for analyzing these data. They show that the choice of strategy can affect inferences about parameters, and hence conclusions drawn from analyses. They discuss the advantages o

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2

Francisco, Carol A., and Wayne A. Fuller. "Quantile Estimation with a Complex Survey Design." Annals of Statistics 19, no. 1 (1991): 454–69. http://dx.doi.org/10.1214/aos/1176347993.

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Zhao, Hu, Cheng Yin, Ming-Sheng Wu, Xiao-Hua Wu, and Shu-Lin Pan. "Research on seismic survey design for doubly complex areas." Applied Geophysics 9, no. 3 (2012): 279–85. http://dx.doi.org/10.1007/s11770-012-0326-4.

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4

Norton, Edward C., Nathan W. Carroll, Morgen M. Miller, Kasey Coyne, Jason J. Wang, and Lawrence C. Kleinman. "Computing risk ratios from data with complex survey design." Health Services and Outcomes Research Methodology 14, no. 1-2 (2014): 3–14. http://dx.doi.org/10.1007/s10742-014-0114-0.

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Barbosa, Flávia dos Santos, Rosely Sichieri, and Washington Leite Junger. "Assessing usual dietary intake in complex sample design surveys: the National Dietary Survey." Revista de Saúde Pública 47 (February 2013): 171s—176s. http://dx.doi.org/10.1590/s0034-89102013000200003.

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Barbosa, Flávia dos Santos, Rosely Sichieri, and Washington Leite Junger. "Assessing usual dietary intake in complex sample design surveys: the National Dietary Survey." Revista de Saúde Pública 47, suppl 1 (2013): 171s—176s. http://dx.doi.org/10.1590/s0034-89102013000700003.

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The National Cancer Institute (NCI) method allows the distributions of usual intake of nutrients and foods to be estimated. This method can be used in complex surveys. However, the user must perform additional calculations, such as balanced repeated replication (BRR), in order to obtain standard errors and confidence intervals for the percentiles and mean from the distribution of usual intake. The objective is to highlight adaptations of the NCI method using data from the National Dietary Survey. The application of the NCI method was exemplified analyzing the total energy (kcal) and fruit (g)

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Dülmer, Hermann. "The Factorial Survey." Sociological Methods & Research 45, no. 2 (2015): 304–47. http://dx.doi.org/10.1177/0049124115582269.

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The factorial survey is an experimental design consisting of varying situations (vignettes) that have to be judged by respondents. For more complex research questions, it quickly becomes impossible for an individual respondent to judge all vignettes. To overcome this problem, random designs are recommended most of the time, whereas quota designs are not discussed at all. First comparisons of random designs with fractional factorial and D-efficient designs are based on fictitious data, first comparisons with fractional factorial and confounded factorial designs are restricted to theoretical con

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Park, Inho. "A study on design effect models for complex sample survey." Journal of the Korean Data and Information Science Society 25, no. 3 (2014): 523–31. http://dx.doi.org/10.7465/jkdi.2014.25.3.523.

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9

Skinner, Chris, and Jon Wakefield. "Introduction to the Design and Analysis of Complex Survey Data." Statistical Science 32, no. 2 (2017): 165–75. http://dx.doi.org/10.1214/17-sts614.

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Stukalov, S. B., D. S. Stukalov, V. I. Kondrikov, and R. S. Gavryushin. "Electrooptical complex for terrain on-time survey." Civil Aviation High Technologies 22, no. 5 (2019): 107–16. http://dx.doi.org/10.26467/2079-0619-2019-22-5-107-116.

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The article deals with a number of approaches to the use of electrooptical systems and unmanned aerial vehicles (UAV) to solve the tasks of live terrain surface screening, air incident spots and objects survey. The paper provides the grounds for the UAV airframe chosen structure and the design of the electrooptical complex. The light weight, high -wing monoplane airframe structure is suggested. Using the CNC production center, a UAV with high aerodynamic performance was developed. The UAV was fitted with the optoelectronic system. Structural design for the airborne and ground equipment of the

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Liu, Fan, Ye Zhang, Chen Zheng, Xiansheng Qin, and Benoît Eynard. "Survey of Configuration Design Approaches: A Focus on Design of Complex Industrial Manufacturing Systems." Procedia CIRP 81 (2019): 340–45. http://dx.doi.org/10.1016/j.procir.2019.03.059.

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12

Arnab, Raghunath, T. Zewotir, and D. North. "Variance Estimation from Complex Survey Designs: A Case Study of Household Income and Expenditure Survey Design 2002/03, Botswana." Communications in Statistics - Theory and Methods 44, no. 1 (2014): 63–79. http://dx.doi.org/10.1080/03610926.2012.731130.

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Burger, Joep, Koen Perryck, and Barry Schouten. "Robustness of Adaptive Survey Designs to Inaccuracy of Design Parameters." Journal of Official Statistics 33, no. 3 (2017): 687–708. http://dx.doi.org/10.1515/jos-2017-0032.

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Abstract Adaptive survey designs (ASDs) optimize design features, given 1) the interactions between the design features and characteristics of sampling units and 2) a set of constraints, such as a budget and a minimum number of respondents. Estimation of the interactions is subject to both random and systematic error. In this article, we propose and evaluate four viewpoints to assess robustness of ASDs to inaccuracy of design parameter estimates: the effect of both imprecision and bias on both ASD structure and ASD performance. We additionally propose three distance measures to compare the str

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14

Heeringa, Steven G., and Jinyun Liu. "Complex sample design effects and inference for mental health survey data." International Journal of Methods in Psychiatric Research 7, no. 1 (1998): 56–65. http://dx.doi.org/10.1002/mpr.34.

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15

Birrell, Carole L., David G. Steel, Marijka J. Batterham, and Ankur Arya. "How to use replicate weights in health survey analysis using the National Nutrition and Physical Activity Survey as an example." Public Health Nutrition 22, no. 18 (2019): 3315–26. http://dx.doi.org/10.1017/s1368980019001927.

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AbstractObjective:To conduct nutrition-related analyses on large-scale health surveys, two aspects of the survey must be incorporated into the analysis: the sampling weights and the sample design; a practice which is not always observed. The present paper compares three analyses: (1) unweighted; (2) weighted but not accounting for the complex sample design; and (3) weighted and accounting for the complex design using replicate weights.Design:Descriptive statistics are computed and a logistic regression investigation of being overweight/obese is conducted using Stata.Setting:Cross-sectional hea

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Yang, D. Aaron, and Richard A. Laven. "Design-Based Approach for Analysing Survey Data in Veterinary Research." Veterinary Sciences 8, no. 6 (2021): 105. http://dx.doi.org/10.3390/vetsci8060105.

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Sample surveys are an essential approach used in veterinary research and investigation. A sample obtained from a well-designed sampling process along with robust data analysis can provide valuable insight into the attributes of the target population. Two approaches, design-based or model-based, can be used as inferential frameworks for analysing survey data. Compared to the model-based approach, the design-based approach is usually more straightforward and directly makes inferences about the finite target population (such as the dairy cows in a herd or dogs in a region) rather than an infinite

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Shetty, Devdas, Lou Manzione, and Ahad Ali. "Survey of Mechatronic Techniques in Modern Machine Design." Journal of Robotics 2012 (2012): 1–9. http://dx.doi.org/10.1155/2012/932305.

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Increasing demands on the productivity of complex systems, such as manufacturing machines and their steadily growing technological importance will require the application of new methods in the product development process. A smart machine can make decisions about the process in real-time with plenty of adaptive controls. This paper shows the simulation based mechatronic model of a complex system with a better understanding of the dynamic behavior and interactions of the components. This offers improved possibilities of evaluating and optimizing the dynamic motion performance of the entire autom

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SeethaLekshmi, Sunil, A. R. Ramya, M. L. P. Reddy, and Sunil Varughese. "Lanthanide complex-derived white-light emitting solids: A survey on design strategies." Journal of Photochemistry and Photobiology C: Photochemistry Reviews 33 (December 2017): 109–31. http://dx.doi.org/10.1016/j.jphotochemrev.2017.11.001.

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19

Rozi, D. S., D. S. Mahmud, and D. G. Lancaster. "Determinants of Health Seeking Behavior in Pakistan: A Complex Health Survey Design." International Journal of Epidemiology 44, suppl_1 (2015): i156. http://dx.doi.org/10.1093/ije/dyv096.197.

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20

Kott, Phillip S. "A design-sensitive approach to fitting regression models with complex survey data." Statistics Surveys 12 (2018): 1–17. http://dx.doi.org/10.1214/17-ss118.

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21

West, Brady T., and Sean Esteban McCabe. "Incorporating Complex Sample Design Effects when Only Final Survey Weights are Available." Stata Journal: Promoting communications on statistics and Stata 12, no. 4 (2012): 718–25. http://dx.doi.org/10.1177/1536867x1201200410.

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22

Caudill, Samuel P. "Confidence interval estimation for pooled-sample biomonitoring from a complex survey design." Environment International 85 (December 2015): 40–45. http://dx.doi.org/10.1016/j.envint.2015.08.003.

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23

Pan, Yi, Samuel P. Caudill, Ruosha Li, and Kathleen L. Caldwell. "Median and quantile tests under complex survey design using SAS and R." Computer Methods and Programs in Biomedicine 117, no. 2 (2014): 292–97. http://dx.doi.org/10.1016/j.cmpb.2014.07.007.

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24

Zou, Danjie, Jennifer E. V. Lloyd, and Jennifer L. Baumbusch. "Using SPSS to Analyze Complex Survey Data: A Primer." Journal of Modern Applied Statistical Methods 18, no. 1 (2020): 2–22. http://dx.doi.org/10.22237/jmasm/1556670300.

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An introduction to using SPSS to analyze complex survey data is given. Key features of complex survey design are described briefly, including stratification, clustering, multiple stages, and weights. Then, annotated SPSS syntax for complex survey data analysis is presented to demonstrate the step-by-step process using real complex samples data.

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Zhou, Hanzhi, Michael R. Elliott, and Trivellore E. Raghunathan. "Synthetic Multiple-Imputation Procedure for Multistage Complex Samples." Journal of Official Statistics 32, no. 1 (2016): 231–56. http://dx.doi.org/10.1515/jos-2016-0011.

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Abstract Multiple imputation (MI) is commonly used when item-level missing data are present. However, MI requires that survey design information be built into the imputation models. For multistage stratified clustered designs, this requires dummy variables to represent strata as well as primary sampling units (PSUs) nested within each stratum in the imputation model. Such a modeling strategy is not only operationally burdensome but also inferentially inefficient when there are many strata in the sample design. Complexity only increases when sampling weights need to be modeled. This article dev

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Chun, Asaph Young, Steven G. Heeringa, and Barry Schouten. "Responsive and Adaptive Design for Survey Optimization." Journal of Official Statistics 34, no. 3 (2018): 581–97. http://dx.doi.org/10.2478/jos-2018-0028.

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Abstract We discuss an evidence-based approach to guiding real-time design decisions during the course of survey data collection. We call it responsive and adaptive design (RAD), a scientific framework driven by cost-quality tradeoff analysis and optimization that enables the most efficient production of high-quality data. The notion of RAD is not new; nor is it a silver bullet to resolve all the difficulties of complex survey design and challenges. RAD embraces precedents and variants of responsive design and adaptive design that survey designers and researchers have practiced over decades. I

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27

Rueda, María del Mar, Beatriz Cobo, and Antonio Arcos. "Regression Models in Complex Survey Sampling for Sensitive Quantitative Variables." Mathematics 9, no. 6 (2021): 609. http://dx.doi.org/10.3390/math9060609.

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Randomized response (RR) techniques are widely used in research involving sensitive variables, such as drugs, violence or crime, especially when a population mean or prevalence must be estimated. However, they are not generally applied to examine relationships between a sensitive variable and other characteristics. This type of technique was initially applied to qualitative variables, and studies later showed that a logistic regression may be performed with RR data. Since many of the variables considered in this context are quantitative, RR techniques were extended to these cases to estimate t

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Gamson, David A., Sarah Anne Eckert, and Jeremy Anderson. "Standards, instructional objectives and curriculum design: A complex relationship." Phi Delta Kappan 100, no. 6 (2019): 8–12. http://dx.doi.org/10.1177/0031721719834022.

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Since the beginning of U.S. public school systems, educators and policy makers have debated what kinds of knowledge and skills that all schoolchildren should acquire. And those debates touch every aspect of a curriculum, its assessment, and its instructional materials. David A. Gamson, Sarah Anne Eckert, and Jeremy Anderson trace the history of standards and objectives in U.S. education, noting areas of controversy and debate related to the uses and possible abuses of curricular standards. Their survey raises questions and cautions for today’s reformers to consider when rethinking curricula.

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Sakshaug, Joseph W., and Brady T. West. "Important Considerations When Analyzing Health Survey Data Collected Using a Complex Sample Design." American Journal of Public Health 104, no. 1 (2014): 15–16. http://dx.doi.org/10.2105/ajph.2013.301515.

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30

Burden, Sandy, Yasmine Probst, David Steel, and Linda Tapsell. "The impact of complex survey design on prevalence estimates of intakes of food groups in the Australian National Children's Nutrition and Physical Activity Survey." Public Health Nutrition 15, no. 8 (2011): 1362–72. http://dx.doi.org/10.1017/s1368980011003326.

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AbstractObjectiveTo assess the impact of the complex survey design used in the 2007 Australian National Children's Nutrition and Physical Activity Survey (ANCNPAS07) on prevalence estimates for intakes of groups of foods in the population of children.DesignThe impacts on prevalence estimates were determined by calculating design effects for values for food group consumption. The implications of ignoring elements of the sample design including stratification, clustering and weighting are discussed.SettingThe ANCNPAS07 used a complex sample design involving stratification, a high degree of clust

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Franco, Carolina, Roderick J. A. Little, Thomas A. Louis, and Eric V. Slud. "Comparative Study of Confidence Intervals for Proportions in Complex Sample Surveys†." Journal of Survey Statistics and Methodology 7, no. 3 (2019): 334–64. http://dx.doi.org/10.1093/jssam/smy019.

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Abstract The most widespread method of computing confidence intervals (CIs) in complex surveys is to add and subtract the margin of error (MOE) from the point estimate, where the MOE is the estimated standard error multiplied by the suitable Gaussian quantile. This Wald-type interval is used by the American Community Survey (ACS), the largest US household sample survey. For inferences on small proportions with moderate sample sizes, this method often results in marked under-coverage and lower CI endpoint less than 0. We assess via simulation the coverage and width, in complex sample surveys, o

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Brosnan, Kylie, Bettina Grün, and Sara Dolnicar. "Cognitive load reduction strategies in questionnaire design." International Journal of Market Research 63, no. 2 (2021): 125–33. http://dx.doi.org/10.1177/1470785320986797.

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Survey data quality suffers when respondents have difficulty completing complex tasks in questionnaires. Cognitive load theory informed the development of strategies for educators to reduce the cognitive load of learning tasks. We investigate whether these cognitive load reduction strategies can be used in questionnaire design to reduce task difficulty and, in so doing, improve survey data quality. We find that this is not the case and conclude that some of the traditional survey answer formats, such as grid questions, which have been criticized in the past lead to equally good data and do not

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Placencia, Juan Pablo Yepez, Jim Murphy, and Dale Carnegie. "Survey of Hardware and Software Design Approaches for Mechatronic Chordophones." Computer Music Journal 43, no. 1 (2020): 38–58. http://dx.doi.org/10.1162/comj_a_00499.

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Mechatronic instruments can create complex sounds that computers and digital instruments have yet to offer. As a specific example, we explore mechatronic chordophones, which use strings as a sound generator and offer a wide array of parametric affordances. The purpose of this work is to review recent approaches for chordophone design and construction, and present current, state-of-the-art devices. We explore multiple mechatronic frames and their components, and we analyze the challenges of building and interacting with these machines. Finally, we review software and hardware approaches that ha

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Davern, Michael, Arthur Jones, James Lepkowski, Gestur Davidson, and Lynn A. Blewett. "Unstable Inferences? An Examination of Complex Survey Sample Design Adjustments Using the Current Population Survey for Health Services Research." INQUIRY: The Journal of Health Care Organization, Provision, and Financing 43, no. 3 (2006): 283–97. http://dx.doi.org/10.5034/inquiryjrnl_43.3.283.

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35

Chaudhuri, Arijit. "Estimation from an Under-Covered Sample in a Complex Survey for Auditing." Calcutta Statistical Association Bulletin 54, no. 1-2 (2003): 115–20. http://dx.doi.org/10.1177/0008068320030110.

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We encounter a practical problem when from a finite population a complex survey design justifies selection of a sample in five stages. The design stipulates selecting a specified number of n(> 2) first stage units by Rao, Hartley and Cochran's (RHC, 1962) scheme followed by simple random sampling (SRS) without replacement (WOR) in each of the four subsequent stages. At the implementation stage a resource crunch calls for reducing the first stage sample size from n to m ( m < n). The consequential modifications in the methods of estimation of population total, mean and ratio of two totals

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McDowell, Allen, and Jeff Pitblado. "From the Help Desk: It's all about the Sampling." Stata Journal: Promoting communications on statistics and Stata 2, no. 2 (2002): 190–201. http://dx.doi.org/10.1177/1536867x0200200207.

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Effective estimation and inference, when the data are collected using complex survey designs, requires estimators that fully account for the sampling design. This article explores, by means of Monte Carlo simulations of the power of simple hypothesis tests, the consequences of parameter estimation and inference when naive estimators are employed with survey data.

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Haslett, Stephen. "Best linear unbiased estimation for varying probability with and without replacement sampling." Special Matrices 7, no. 1 (2019): 78–91. http://dx.doi.org/10.1515/spma-2019-0007.

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Abstract When sample survey data with complex design (stratification, clustering, unequal selection or inclusion probabilities, and weighting) are used for linear models, estimation of model parameters and their covariance matrices becomes complicated. Standard fitting techniques for sample surveys either model conditional on survey design variables, or use only design weights based on inclusion probabilities essentially assuming zero error covariance between all pairs of population elements. Design properties that link two units are not used. However, if population error structure is correlat

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Chung, Chin-Eun. "Complex sample design effects and inference for Korea National Health and Nutrition Examination Survey data." Korean Journal of Nutrition 45, no. 6 (2012): 600. http://dx.doi.org/10.4163/kjn.2012.45.6.600.

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Matsiy, Sergey, and Vladimir Matsiy. "Landslide protection of the ski resort “Mountain Air” on the Sakhalin Island." MATEC Web of Conferences 265 (2019): 04013. http://dx.doi.org/10.1051/matecconf/201926504013.

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This article contains the results of engineering and geological surveys and geotechnical calculations made for the development of the sports complex STK "Mountain Air" in the south-eastern part of Sakhalin Island. Design and survey work is performed, as well as reconstruction and setup of the associated infrastructure of the complex, including the construction of ski slopes and cable-ways. The description of the designed supporting and retaining structures is given.

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Liker, Jeffrey K. "Survey-Guided Change in Ship Design and Production: Prospects and Limitations at U.S. Ship." Journal of Ship Production 4, no. 02 (1988): 81–93. http://dx.doi.org/10.5957/jsp.1988.4.2.81.

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This paper describes and analyzes an attempt to improve the ship design organization of a U.S. shipbuilder guided by data from a survey of the engineering workforce. While the survey was effective in diagnosing social and technological impediments to effectiveness and while it influenced the priorities of a task force established to improve engineering effectiveness, ultimately the task force was dissolved in response to short-term pressures to complete delivery of the first ship on a major contract on schedule. Why was this improvement effort cut short just as it was gaining momentum? The pap

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Zhao, Tian-Fang, Wei-Neng Chen, Xin-Xin Ma, and Xiao-Kun Wu. "Evolutionary Computation in Social Propagation over Complex Networks: A Survey." International Journal of Automation and Computing 18, no. 4 (2021): 503–20. http://dx.doi.org/10.1007/s11633-021-1302-3.

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AbstractSocial propagation denotes the spread phenomena directly correlated to the human world and society, which includes but is not limited to the diffusion of human epidemics, human-made malicious viruses, fake news, social innovation, viral marketing, etc. Simulation and optimization are two major themes in social propagation, where network-based simulation helps to analyze and understand the social contagion, and problem-oriented optimization is devoted to contain or improve the infection results. Though there have been many models and optimization techniques, the matter of concern is tha

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Zhang, Dong Min, Yu Qing Song, and Yu Chun Xu. "Survey of User Needs for Design Knowledge Management for Product Life Cycle." Applied Mechanics and Materials 483 (December 2013): 502–5. http://dx.doi.org/10.4028/www.scientific.net/amm.483.502.

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It is important to develop an application to manage knowledge for reusing as efficiently as possible. Knowledge management in advanced manufacturing industries is a complex process. In this paper, user needs for design knowledge management are gathered from interviews with users and during brainstorming sessions. The main requirements for design knowledge management are such as: design knowledge normalizing, design case normalizing, knowledge tracing, generating know-how knowledge, learning failure case knowledge, and design knowledge management in product lifecycle, etc. Knowledge application

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Wang, Hui, and Zichun Le. "Seven-Layer Model in Complex Networks Link Prediction: A Survey." Sensors 20, no. 22 (2020): 6560. http://dx.doi.org/10.3390/s20226560.

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Link prediction is the most basic and essential problem in complex networks. This study analyzes the observed topological, time, attributive, label, weight, directional, and symbolic features and auxiliary information to find the lack of connection and predict the future possible connection. For discussion and analysis of the evolution of the network, the network model is of great significance. In the past two decades, link prediction has attracted extensive attention from experts in various fields, who have published numerous high-level papers, but few combine interdisciplinary characteristic

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Cho, MoonJung, John L. Eltinge, Julie Gershunskaya, and Larry Huff. "Evaluation of Generalized Variance Functions in the Analysis of Complex Survey Data." Journal of Official Statistics 30, no. 1 (2014): 63–90. http://dx.doi.org/10.2478/jos-2014-0004.

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Abstract Two sets of diagnostics are presented to evaluate the properties of generalized variance functions (GVFs) for a given sample survey. The first set uses test statistics for the coefficients of multiple regression forms of GVF models. The second set uses smoothed estimators of the mean squared error (MSE) of GVF-based variance estimators. The smooth version of the MSE estimator can provide a useful measure of the performance of a GVF estimator, relative to the variance of a standard design-based variance estimator. Some of the proposed methods are applied to sample data from the Current

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Kaminska, Olena, and Peter Lynn. "Survey-Based Cross-Country Comparisons Where Countries Vary in Sample Design: Issues and Solutions." Journal of Official Statistics 33, no. 1 (2017): 123–36. http://dx.doi.org/10.1515/jos-2017-0007.

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Abstract In multi-national surveys, different countries usually implement different sample designs. The sample designs affect the variance of estimates of differences between countries. When making such estimates, analysts often fail to take sufficient account of sample design. This failure occurs sometimes because variables indicating stratification, clustering, or weighting are unavailable, partially available, or in a form that is unsuitable for cross-national analysis. In this article, we demonstrate how complex sample design should be taken into account when estimating differences between

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West, Brady T., Joseph W. Sakshaug, and Guy Alain S. Aurelien. "Accounting for Complex Sampling in Survey Estimation: A Review of Current Software Tools." Journal of Official Statistics 34, no. 3 (2018): 721–52. http://dx.doi.org/10.2478/jos-2018-0034.

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Abstract In this article, we review current state-of-the art software enabling statisticians to apply design-based, model-based, and so-called “hybrid” approaches to the analysis of complex sample survey data. We present brief overviews of the similarities and differences between these alternative approaches, and then focus on software tools that are presently available for implementing each approach. We conclude with a summary of directions for future software development in this area.

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Liu, Haitao, Yew-Soon Ong, and Jianfei Cai. "A survey of adaptive sampling for global metamodeling in support of simulation-based complex engineering design." Structural and Multidisciplinary Optimization 57, no. 1 (2017): 393–416. http://dx.doi.org/10.1007/s00158-017-1739-8.

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48

Toth, Daniell. "A Permutation Test on Complex Sample Data." Journal of Survey Statistics and Methodology 8, no. 4 (2019): 772–91. http://dx.doi.org/10.1093/jssam/smz018.

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Abstract Permutation tests are a distribution-free way of performing hypothesis tests. These tests rely on the condition that the observed data are exchangeable among the groups being tested under the null hypothesis. This assumption is easily satisfied for data obtained from a simple random sample or a controlled study after simple adjustments to the data, but there is no general method for adjusting survey data collected using a complex sample design to allow for permutation tests. In this article, we propose a general method for performing a pseudo-permutation test that accounts for the com

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Wang, Jin Ping. "Survey of Fire Load in Building Furniture Store." Applied Mechanics and Materials 580-583 (July 2014): 2642–45. http://dx.doi.org/10.4028/www.scientific.net/amm.580-583.2642.

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There are many combustible materials in building furniture stores with complex people traffic and high risk of fire disaster. Fire load as the represent of flammable material, and the building fire risk can be grasped by the data obtained. Through investigation and statistics on the fire load density value of building furniture store, it is convenient for performance fire safety design. According to the survey, fire load density average value is determined of 382.71 , the standard deviation is of 143.46 . After fitting the survey data, the data distribution do not refuse to obey the extreme-va

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Waldkoetter, Raymond O., Richard B. Modjeski, and Thomas Curran. "Training Design and Personnel Evaluation of a Training Program." Perceptual and Motor Skills 69, no. 3-1 (1989): 979–89. http://dx.doi.org/10.1177/00315125890693-151.

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Abstract:

Complex issues in training design can occur when a new training program must integrate device/equipment and personnel skills. The Firefinder Simulator, Artillery-Locating Radar System, and Course were analyzed in a specially devised approach to assure training effectiveness. Using qualified personnel for evaluation of course design and performance, a task-oriented questionnaire was given in an interview survey of 53 test-player subjects following a training effectiveness test. Selected results were significantly related to total group analysis reflecting the hypothesized design features and tr

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