Literature DB >> 35292932

DIY bootstrapping: Getting the nonparametric bootstrap confidence interval in SPSS for any statistics or function of statistics (when this bootstrapping is appropriate).

Shu Fai Cheung1, Ivan Jacob Agaloos Pesigan2, Weng Ngai Vong2.   

Abstract

Researchers can generate bootstrap confidence intervals for some statistics in SPSS using the BOOTSTRAP command. However, this command can only be applied to selected procedures, and only to selected statistics in these procedures. We developed an extension command and prepared some sample syntax files based on existing approaches from the Internet to illustrate how researchers can (a) generate a large number of nonparametric bootstrap samples, (b) do desired analysis on all these samples, and (c) form the bootstrap confidence intervals for selected statistics using the OMS commands. We developed these tools to help researchers apply nonparametric bootstrapping to any statistics for which this method is appropriate, including statistics derived from other statistics, such as standardized effect size measures computed from the t test results. We also discussed how researchers can extend the tools for other statistics and scenarios they encounter.
© 2022. The Psychonomic Society, Inc.

Entities:  

Keywords:  Bootstrapping; Confidence intervals; Effect sizes

Year:  2022        PMID: 35292932     DOI: 10.3758/s13428-022-01808-5

Source DB:  PubMed          Journal:  Behav Res Methods        ISSN: 1554-351X


  12 in total

1.  A Comparison of Methods for Constructing Confidence Intervals for the Squared Multiple Correlation Coefficient.

Authors:  J Algina
Journal:  Multivariate Behav Res       Date:  1999-10-01       Impact factor: 5.923

2.  Confidence intervals for correlations when data are not normal.

Authors:  Anthony J Bishara; James B Hittner
Journal:  Behav Res Methods       Date:  2017-02

3.  Antibodies to human immunodeficiency virus in human sera induce cell-mediated lysis of human immunodeficiency virus-infected cells.

Authors:  E A Ojo-Amaize; P Nishanian; D E Keith; R L Houghton; D F Heitjan; J L Fahey; J V Giorgi
Journal:  J Immunol       Date:  1987-10-01       Impact factor: 5.422

4.  Comparison of methods for constructing confidence intervals of standardized indirect effects.

Authors:  Mike W-L Cheung
Journal:  Behav Res Methods       Date:  2009-05

5.  The frequency distribution of the product-moment correlation coefficient in random samples of any size drawn from non-normal universes.

Authors:  A K GAYEN
Journal:  Biometrika       Date:  1951-06       Impact factor: 2.445

Review 6.  Testing the significance of a correlation with nonnormal data: comparison of Pearson, Spearman, transformation, and resampling approaches.

Authors:  Anthony J Bishara; James B Hittner
Journal:  Psychol Methods       Date:  2012-05-07

7.  Computing confidence intervals for standardized regression coefficients.

Authors:  Jeff A Jones; Niels G Waller
Journal:  Psychol Methods       Date:  2013-09-30

8.  Robust statistical methods in R using the WRS2 package.

Authors:  Patrick Mair; Rand Wilcox
Journal:  Behav Res Methods       Date:  2020-04

9.  Reporting effect sizes in original psychological research: A discussion and tutorial.

Authors:  Jolynn Pek; David B Flora
Journal:  Psychol Methods       Date:  2017-03-09

10.  Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations.

Authors:  Sander Greenland; Stephen J Senn; Kenneth J Rothman; John B Carlin; Charles Poole; Steven N Goodman; Douglas G Altman
Journal:  Eur J Epidemiol       Date:  2016-05-21       Impact factor: 8.082

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.