The Jackknife--Toy, Tool or Two-Edged Weapon?

Bissell, A. F.; Ferguson, R. A.

doi:10.2307/2987663

Cited by 42 publications

(17 citation statements)

References 9 publications

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“…If n is much smaller, jackknifing is suggested (cf. Bissell & Ferguson, 1975;Rogers, 1976) as a method for estimation of standard errors, although the functional form of the equations derived from the delta method provides valuable insights, which jackknifing cannot.…”

Section: Discussion and Summary Standard Errorsmentioning

confidence: 99%

Large Sample Estimators for Standard Errors of Functions of Correlation Coefficients

Bobko

Rieck

1980

Applied Psychological Measurement

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Standard errors of estimators that are functions of correlation coefficients are shown to be quite different in magnitude than standard errors of the initial correlations. A general large-sample methodology, based upon Taylor series expansions and asymptotic correlational results, is developed for the computation of such standard errors. Three exemplary analyses are conducted on a correction for attenuation, a correction for range restriction, and an indirect effect in path analysis. Derived formulae are consistent with several previously proposed estimators and provide excellent approximations to the standard errors obtained in computer simulations, even for moderate sample size (n = 100). It is shown that functions of correlations can be considerably more variable than product-moment correlations. Additionally, appropriate hypothesis tests are derived for these corrected coefficients and the indirect effect. It is shown that in the range restriction situation, the appropriate hypothesis test based on the corrected coefficient is asymptotically more powerful than the test utilizing the uncorrected coefficient. Bias is also discussed as a by-product of the methodology.Many estimators in the social sciences are functions of Pearson product-moment correlation coefficients. For example, the correction of a validity coefficient for attenuation due to unreliability is a function of both the original correlation and a reliability estimate. Discussion of the corrected coefficient in its use as a parameter estimate usually revolves around its magnitude and/or practical significance. Therefore, some indication of the standard error of these corrected coefficients is crucial to the interpretability of the findings. That corrected coefficients may be greater than unity (cf. Karren, 1978) also supplies impetus to this investigation.The present paper presents a large-sample methodology for deriving estimates of the standard errors of functions of correlation coefficients. For example, it is shown below that correlations corrected for attenuation are considerably more variable than product-moment correlations. The APA Standards for Educational and Psychological Tests (American Psychological Association, 1974) indicates that &dquo;where correlation coefficients are corrected for attenuation or restriction in range, full information relevant to the correction should be presented&dquo; (Section E8.2.1.). Thus, the derivation of standard errors of these corrected coefficients would represent important progress towards &dquo;full information.&dquo;

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Section: Discussion and Summary Standard Errorsmentioning

confidence: 99%

Large Sample Estimators for Standard Errors of Functions of Correlation Coefficients

Bobko

Rieck

1980

Applied Psychological Measurement

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“…The basic idea behind the jackknife technique is to divide the original set of data into subgroups several times, then systematically recalculate the statistical estimate each time leaving one observations from the sample set out. The objective of the jackknife is to conclude an estimate of the bias and produce an estimate of the variance of the statistic (Bissell and Ferguson, 1975).…”

Section: Resampling Methodsmentioning

confidence: 99%

“…Despite its popularity and efficiency, research has noted some limitations of the jackknife technique, for example Bissell and Ferguson (1975) argue that researchers should avoid relying on jackknifing when data involves order statistics or extreme values.…”

Section: Resampling Methodsmentioning

confidence: 99%

Evaluating classification accuracy: the impact of resampling and dataset size

Imlawi

Alsharo

2017

IJBIS

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Abstract:Correct prediction is important criterion in evaluating classifiers in supervised learning context. The accuracy rate is a widely accepted indicator of the probability of misclassification of a classifier. Nevertheless, true accuracy remains unknown in most cases since it is not always possible to include the whole population in a study, and it is difficult to calculate the probability distribution of the data. Therefore, researchers often rely on computing estimation from the available data through sampling. When the available data is small or limited, it is common to rely on a resampling technique for accuracy estimation. In this paper, we study the impact of the resampling against non-resampling estimation method, with different dataset sizes on the sample distribution variance. Initial results indicate that there is a significant difference in the variance of the sample distribution between resampling and non-resampling. We also found that the larger the dataset size, the less significant the difference in variance.

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“…It can also be generalized for multivariate cases (Van Valen 1978. Van Valen (2005) reviewed the statistics of variation and suggested Levene's test (Levene 1960), Smith's Test (published in Grüneberg et al 1966) and jackknifing (Arvesen and Schmitz 1970;Miller 1974;Bissell and Ferguson 1975), which can be used to compare absolute and relative variation, to be most suitable, depending on the situation (Van Valen 1978. He advised against using the classical F-test for the equality of variances as it is very sensitive to non-normality (Van Valen 2005).…”

Section: Comparing the Range Of Intraspecific Variationmentioning

confidence: 99%

Ammonoid Intraspecific Variability

Baets

Bert

Hoffmann

et al. 2015

Topics in Geobiology

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Because ammonoids have never been observed swimming, there is no alternative to seeking indirect indications of the locomotory abilities of ammonoids. This approach is based on actualistic comparisons with the closest relatives of ammonoids, the Coleoidea and the Nautilida, and on the geometrical and physical properties of the shell. Anatomical comparison yields information on the locomotor muscular systems and organs as well as possible modes of propulsion while the shape and physics of ammonoid shells provide information on buoyancy, shell orientation, drag, added mass, cost of transportation and thus on limits of acceleration and swimming speed. On these grounds, we conclude that ammonoid swimming is comparable to that of Recent nautilids and sepiids in terms of speed and energy consumption, although some ammonoids might have been slower swimmers than nautilids.

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The Jackknife--Toy, Tool or Two-Edged Weapon?

Cited by 42 publications

References 9 publications

Large Sample Estimators for Standard Errors of Functions of Correlation Coefficients

Large Sample Estimators for Standard Errors of Functions of Correlation Coefficients

Evaluating classification accuracy: the impact of resampling and dataset size

Ammonoid Intraspecific Variability

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