Bias in Estimation and Hypothesis Testing of Correlation

By D. W. Zimmerman, Bruno D. Zumbo, Richard H. Williams. 2003

128 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

The proximity effect: The role of inter-item distance on reverse-item bias (2009, background): “stability and reliability ( Zimmerman, Zumbo, & Williams, 2003 ), as did the fact that items were randomly assigned to positions in the questionnaire.”
High Dimensional Semiparametric Gaussian Copula Graphical Models. (2012, methodology): “To prove the desired result, we apply the following bias equation from Zimmerman et al. (2003):”
Geographic effects on American eel (Anguilla rostrata) life history characteristics and strategies (2010, background): “The sample estimate (r) of the Pearson’s correlation coefficient (r) is biased low when sample sizes are less than about 40 (Olkin and Pratt 1958; Zimmerman et al. 2003), which may be particularly important if r is marginally nonsignificant (statistical significance accepted at a = 0.”
Evaluation of model quality predictions in CASP9 (2011, methodology): “26 The raw results of the correlation analyses are available at http://predictioncen-ter.org/casp9/qa_analysis.cgi.”
Comparing the Pearson and Spearman correlation coefficients across distributions and sample sizes: A tutorial using simulations and empirical data. (2016, background): “Equation 6 provides the expected value of rp (Ghosh, 1966), while Equation 7 provides the expected value of rs (Moran, 1948; Xu et al., 2013; Zimmerman et al., 2003).”