The Pearson r-from-Z approximation estimates the sample correlation (as an effect size measure) from the ratio of two quantities: the standard normal deviate equivalent (Z-score) corresponding to a one-tailed p-value divided by the square root of the total (pooled) sample size. The formula has utility in meta-analytic work when reports of research contain minimal statistical information. Although simple to implement, the accuracy of the Pearson r-from-Z approximation has not been empirically evaluated. To address this omission, we performed a series of Monte Carlo simulations. Results indicated that in some cases the formula did accurately estimate the sample correlation. However, when sample size was very small (N = 10) and effect sizes were small to small-moderate (ds of 0.1 and 0.3), the Pearson r-from-Z approximation was very inaccurate. Detailed figures that provide guidance as to when the Pearson r-from-Z formula will likely yield valid inferences are presented.
Description
How accurate is the Pearson r-from-Z approximation? A Monte Carlo simulation study. - PubMed - NCBI
%0 Journal Article
%1 Hittner:2012:J-Gen-Psychol:24836910
%A Hittner, J B
%A May, K
%D 2012
%J J Gen Psychol
%K statistics
%N 2
%P 68-77
%R 10.1080/00221309.2012.661376
%T How accurate is the Pearson r-from-Z approximation? A Monte Carlo simulation study
%U https://www.ncbi.nlm.nih.gov/pubmed/24836910
%V 139
%X The Pearson r-from-Z approximation estimates the sample correlation (as an effect size measure) from the ratio of two quantities: the standard normal deviate equivalent (Z-score) corresponding to a one-tailed p-value divided by the square root of the total (pooled) sample size. The formula has utility in meta-analytic work when reports of research contain minimal statistical information. Although simple to implement, the accuracy of the Pearson r-from-Z approximation has not been empirically evaluated. To address this omission, we performed a series of Monte Carlo simulations. Results indicated that in some cases the formula did accurately estimate the sample correlation. However, when sample size was very small (N = 10) and effect sizes were small to small-moderate (ds of 0.1 and 0.3), the Pearson r-from-Z approximation was very inaccurate. Detailed figures that provide guidance as to when the Pearson r-from-Z formula will likely yield valid inferences are presented.
@article{Hittner:2012:J-Gen-Psychol:24836910,
abstract = {The Pearson r-from-Z approximation estimates the sample correlation (as an effect size measure) from the ratio of two quantities: the standard normal deviate equivalent (Z-score) corresponding to a one-tailed p-value divided by the square root of the total (pooled) sample size. The formula has utility in meta-analytic work when reports of research contain minimal statistical information. Although simple to implement, the accuracy of the Pearson r-from-Z approximation has not been empirically evaluated. To address this omission, we performed a series of Monte Carlo simulations. Results indicated that in some cases the formula did accurately estimate the sample correlation. However, when sample size was very small (N = 10) and effect sizes were small to small-moderate (ds of 0.1 and 0.3), the Pearson r-from-Z approximation was very inaccurate. Detailed figures that provide guidance as to when the Pearson r-from-Z formula will likely yield valid inferences are presented.},
added-at = {2019-11-04T20:56:57.000+0100},
author = {Hittner, J B and May, K},
biburl = {https://www.bibsonomy.org/bibtex/2acdc6613550cb8b09d654de0847d5f9f/jkd},
description = {How accurate is the Pearson r-from-Z approximation? A Monte Carlo simulation study. - PubMed - NCBI},
doi = {10.1080/00221309.2012.661376},
interhash = {d078275b8d59c730325051c407624038},
intrahash = {acdc6613550cb8b09d654de0847d5f9f},
journal = {J Gen Psychol},
keywords = {statistics},
month = {Apr-Jun},
number = 2,
pages = {68-77},
pmid = {24836910},
timestamp = {2019-11-04T20:56:57.000+0100},
title = {How accurate is the Pearson r-from-Z approximation? A Monte Carlo simulation study},
url = {https://www.ncbi.nlm.nih.gov/pubmed/24836910},
volume = 139,
year = 2012
}