"Resampling methods: Concepts, Applications, and Justification"

In recent years many emerging statistical analytical tools, such as exploratory data analysis (EDA), data visualization, robust procedures, and resampling methods, have been gaining attention among psychological and educational researchers. However, many researchers tend to embrace traditional statistical methods rather than experimenting with these new techniques, even though the data structure does not meet certain parametric assumptions. Three factors contribute to this conservative practice. First, newer methods are generally not included in statistics courses, and as a result, the concepts of these newer methods seem obscure to many people. Second, in the past most software developers devoted efforts to program statistical packages for conventional data analysis. Even if researchers are aware of these new techniques, the limited software availability hinders them from implementing them. Last, even with awareness of these concepts and access to software, some researchers hesitate to apply "marginal" procedures. Traditional procedures are perceived as founded on solid theoretical justification and empirical substantiation, while newer techniques face harsh criticisms and seem to be lacking theoretical support. Resampling methods: concepts, applications, and justification. Yu, Chong Ho http://pareonline.net/getvn.asp?v=8&n=19

[1]  M. S. Bartlett,et al.  Statistical methods and scientific inference. , 1957 .

[2]  P. Good,et al.  Permutation Tests: A Practical Guide to Resampling Methods for Testing Hypotheses , 1995 .

[3]  Ivars Peterson,et al.  Pick a Sample. , 1991 .

[4]  A. K. Kurtz.  A Research Test of the Rorschach Test , 1948 .

[5]  Scott M. Smith,et al.  Computer Intensive Methods for Testing Hypotheses: An Introduction , 1989 .

[6]  E. Ziegel,et al.  Bootstrapping: A Nonparametric Approach to Statistical Inference , 1993 .

[7]  Patricia Snyder,et al.  Statistical Significance Testing Practices in The Journal of Experimental Education , 1997 .

[8]  Ronald N. Giere,et al.  Progress and its problems: Toward a theory of scientific growth , 1978 .

[9]  M. H. Quenouille.  Approximate Tests of Correlation in Time‐Series , 1949 .

[10]  Rebecca P. Ang,et al.  Use of the Jackknife Statistic to Evaluate Result Replicability , 1998 .

[11]  Chong Ho Yu,et al.  Impact of Asynchronous and Synchronous Internet-Based Communication on Collaboration and Performance among K-12 Teachers , 2000 .

[12]  S. S. Young,et al.  Resampling-Based Multiple Testing: Examples and Methods for p-Value Adjustment , 1993 .

[13]  Chong Ho Alex Yu,et al.  HIV-risk behaviours of American spring break vacationers: a case of situational disinhibition? , 2002, International journal of STD & AIDS.

[14]  Léopold Simar,et al.  Computer Intensive Methods in Statistics , 1994 .

[15]  Thomas R. Willemain,et al.  Bootstrap on a Shoestring: Resampling Using Spreadsheets , 1994 .

[16]  Lawrence M. Rudner,et al.  Resampling: A Marriage of Computers and Statistics , 1991 .

[17]  Donald Nute,et al.  Counterfactuals , 1975, Notre Dame J. Formal Log..

[18]  C. I. Mosier.  I. Problems and Designs of Cross-Validation 1 , 1951 .

[19]  Harald Bergstriim.  Mathematical Theory of Probability and Statistics , 1966 .

[20]  Thomas M. Loughin,et al.  Data Analysis by Resampling: Concepts and Applications , 2001, Technometrics.

[21]  B. Efron.  The jackknife, the bootstrap, and other resampling plans , 1987 .

[22]  H. Reichenbach.  Experience and Prediction. An Analysis of the Foundations and the Structure of Knowledge , 1938 .

[23]  B. Efron.  Nonparametric estimates of standard error: The jackknife, the bootstrap and other methods , 1981 .

[24]  Barbara A. Price,et al.  A Spreadsheet Approach to Teaching Resampling , 1998 .

[25]  Clay Helberg,et al.  Pitfalls of Data Analysis , 1996 .

[26]  A. A..  Probability, Statistics and Truth , 1940, Nature.

[27]  J. Rodgers,et al.  The Bootstrap, the Jackknife, and the Randomization Test: A Sampling Taxonomy. , 1999, Multivariate behavioral research.

[28]  Xitao Fan,et al.  Comparability of Jackknife and Bootstrap Results: An Investigation for a Case of Canonical Correlation Analysis. , 1996 .

[29]  D. Krus,et al.  Computer Assisted Multicrossvalidation in Regression Analysis , 1982 .

[30]  J. Simon.  Resampling: The new statistics , 1995 .

[31]  James M. Joyce.  Interpreting Probability: Controversies and Developments in the Early Twentieth Century , 2004 .

[32]  John Ludbrook,et al.  Why Permutation Tests are Superior to t and F Tests in Biomedical Research , 1998 .