This (method) is (not) fine

Research output: Contribution to journalComment/Letter to the editorScientificpeer-review

Abstract

SummaryIn their response to my criticism of their recent article in Journal of Biosocial Science (te Nijenhuis et al., 2017), te Nijenhuis and van den Hoek (2018) raise four points none of which concerns my main point that the method of correlated vectors (MCV) applied to item-level data represents a flawed method. Here, I discuss te Nijenhuis and van den Hoek's four points. First, I argue that my previous application of MCV to item-level data showed that the method can yield nonsensical results. Second, I note that meta-analytic corrections for sampling error, imperfect measures, restriction of range and unreliability of the vectors are futile and cannot help fix the method. Third, I note that even with perfect data, the method can yield negative correlations. Fourth, I highlight the irrelevance of te Nijenhuis and van den Hoek (2018)'s point that my comment had not been published in a peerreviewed journal by referring to my articles in 2009 and 2017 on MCV in peer-reviewed journals.

Original languageEnglish
Pages (from-to)872-874
JournalJournal of Biosocial Science
Volume50
Issue number6
DOIs
Publication statusPublished - 2018

Fingerprint

Selection Bias

Cite this

@article{0210f4b619864d168ee1be089243f609,
title = "This (method) is (not) fine",
abstract = "SummaryIn their response to my criticism of their recent article in Journal of Biosocial Science (te Nijenhuis et al., 2017), te Nijenhuis and van den Hoek (2018) raise four points none of which concerns my main point that the method of correlated vectors (MCV) applied to item-level data represents a flawed method. Here, I discuss te Nijenhuis and van den Hoek's four points. First, I argue that my previous application of MCV to item-level data showed that the method can yield nonsensical results. Second, I note that meta-analytic corrections for sampling error, imperfect measures, restriction of range and unreliability of the vectors are futile and cannot help fix the method. Third, I note that even with perfect data, the method can yield negative correlations. Fourth, I highlight the irrelevance of te Nijenhuis and van den Hoek (2018)'s point that my comment had not been published in a peerreviewed journal by referring to my articles in 2009 and 2017 on MCV in peer-reviewed journals.",
author = "Wicherts, {Jelte M}",
year = "2018",
doi = "10.1017/S0021932018000184",
language = "English",
volume = "50",
pages = "872--874",
journal = "Journal of Biosocial Science",
issn = "0021-9320",
publisher = "Cambridge University Press",
number = "6",

}

This (method) is (not) fine. / Wicherts, Jelte M.

In: Journal of Biosocial Science, Vol. 50, No. 6, 2018, p. 872-874.

Research output: Contribution to journalComment/Letter to the editorScientificpeer-review

TY - JOUR

T1 - This (method) is (not) fine

AU - Wicherts, Jelte M

PY - 2018

Y1 - 2018

N2 - SummaryIn their response to my criticism of their recent article in Journal of Biosocial Science (te Nijenhuis et al., 2017), te Nijenhuis and van den Hoek (2018) raise four points none of which concerns my main point that the method of correlated vectors (MCV) applied to item-level data represents a flawed method. Here, I discuss te Nijenhuis and van den Hoek's four points. First, I argue that my previous application of MCV to item-level data showed that the method can yield nonsensical results. Second, I note that meta-analytic corrections for sampling error, imperfect measures, restriction of range and unreliability of the vectors are futile and cannot help fix the method. Third, I note that even with perfect data, the method can yield negative correlations. Fourth, I highlight the irrelevance of te Nijenhuis and van den Hoek (2018)'s point that my comment had not been published in a peerreviewed journal by referring to my articles in 2009 and 2017 on MCV in peer-reviewed journals.

AB - SummaryIn their response to my criticism of their recent article in Journal of Biosocial Science (te Nijenhuis et al., 2017), te Nijenhuis and van den Hoek (2018) raise four points none of which concerns my main point that the method of correlated vectors (MCV) applied to item-level data represents a flawed method. Here, I discuss te Nijenhuis and van den Hoek's four points. First, I argue that my previous application of MCV to item-level data showed that the method can yield nonsensical results. Second, I note that meta-analytic corrections for sampling error, imperfect measures, restriction of range and unreliability of the vectors are futile and cannot help fix the method. Third, I note that even with perfect data, the method can yield negative correlations. Fourth, I highlight the irrelevance of te Nijenhuis and van den Hoek (2018)'s point that my comment had not been published in a peerreviewed journal by referring to my articles in 2009 and 2017 on MCV in peer-reviewed journals.

U2 - 10.1017/S0021932018000184

DO - 10.1017/S0021932018000184

M3 - Comment/Letter to the editor

VL - 50

SP - 872

EP - 874

JO - Journal of Biosocial Science

JF - Journal of Biosocial Science

SN - 0021-9320

IS - 6

ER -