Publication

Improving confidence intervals for normed test scores: Include uncertainty due to sampling variability

Voncken, L., Albers, C. J. & Timmerman, M. E., Apr-2019, In : Behavior Research Methods. 51, 2, p. 826–839 14 p.

Research output: Contribution to journalArticleAcademicpeer-review

APA

Voncken, L., Albers, C. J., & Timmerman, M. E. (2019). Improving confidence intervals for normed test scores: Include uncertainty due to sampling variability. Behavior Research Methods, 51(2), 826–839. https://doi.org/10.3758/s13428-018-1122-8

Author

Voncken, Lieke ; Albers, Casper J. ; Timmerman, Marieke E. / Improving confidence intervals for normed test scores : Include uncertainty due to sampling variability. In: Behavior Research Methods. 2019 ; Vol. 51, No. 2. pp. 826–839.

Harvard

Voncken, L, Albers, CJ & Timmerman, ME 2019, 'Improving confidence intervals for normed test scores: Include uncertainty due to sampling variability', Behavior Research Methods, vol. 51, no. 2, pp. 826–839. https://doi.org/10.3758/s13428-018-1122-8

Standard

Improving confidence intervals for normed test scores : Include uncertainty due to sampling variability. / Voncken, Lieke; Albers, Casper J.; Timmerman, Marieke E.

In: Behavior Research Methods, Vol. 51, No. 2, 04.2019, p. 826–839.

Research output: Contribution to journalArticleAcademicpeer-review

Vancouver

Voncken L, Albers CJ, Timmerman ME. Improving confidence intervals for normed test scores: Include uncertainty due to sampling variability. Behavior Research Methods. 2019 Apr;51(2):826–839. https://doi.org/10.3758/s13428-018-1122-8


BibTeX

@article{e7a57ca39d9e4f55a94d51aeef179d85,
title = "Improving confidence intervals for normed test scores: Include uncertainty due to sampling variability",
abstract = "Test publishers usually provide confidence intervals (CIs) for normed test scores that reflect the uncertainty due to the unreliability of the tests. The uncertainty due to sampling variability in the norming phase is ignored. To express uncertainty due to norming, we propose a flexible method that is applicable in continuous norming and allows for a variety of score distributions, using Generalized Additive Models for Location, Scale, and Shape (GAMLSS; Rigby & Stasinopoulos, 2005). We assessed the performance of this method in a simulation study, by examining the quality of the resulting CIs. We varied the population model, procedure of estimating the CI, confidence level, sample size, value of the predictor, extremity of the test score, and type of variance-covariance matrix. The results showed that good quality of the CIs could be achieved in most conditions. The method is illustrated using normative data of the SON-R 6-40 test. We recommend test developers to use this approach to arrive at CIs, and thus properly express the uncertainty due to norm sampling fluctuations, in the context of continuous norming. Adopting this approach will help (e.g., clinical) practitioners to obtain a fair picture of the person assessed.",
keywords = "CORRELATION MATRIX",
author = "Lieke Voncken and Albers, {Casper J.} and Timmerman, {Marieke E.}",
year = "2019",
month = "4",
doi = "10.3758/s13428-018-1122-8",
language = "English",
volume = "51",
pages = "826–839",
journal = "Behavior Research Methods",
issn = "1554-351X",
publisher = "SPRINGER",
number = "2",

}

RIS

TY - JOUR

T1 - Improving confidence intervals for normed test scores

T2 - Include uncertainty due to sampling variability

AU - Voncken, Lieke

AU - Albers, Casper J.

AU - Timmerman, Marieke E.

PY - 2019/4

Y1 - 2019/4

N2 - Test publishers usually provide confidence intervals (CIs) for normed test scores that reflect the uncertainty due to the unreliability of the tests. The uncertainty due to sampling variability in the norming phase is ignored. To express uncertainty due to norming, we propose a flexible method that is applicable in continuous norming and allows for a variety of score distributions, using Generalized Additive Models for Location, Scale, and Shape (GAMLSS; Rigby & Stasinopoulos, 2005). We assessed the performance of this method in a simulation study, by examining the quality of the resulting CIs. We varied the population model, procedure of estimating the CI, confidence level, sample size, value of the predictor, extremity of the test score, and type of variance-covariance matrix. The results showed that good quality of the CIs could be achieved in most conditions. The method is illustrated using normative data of the SON-R 6-40 test. We recommend test developers to use this approach to arrive at CIs, and thus properly express the uncertainty due to norm sampling fluctuations, in the context of continuous norming. Adopting this approach will help (e.g., clinical) practitioners to obtain a fair picture of the person assessed.

AB - Test publishers usually provide confidence intervals (CIs) for normed test scores that reflect the uncertainty due to the unreliability of the tests. The uncertainty due to sampling variability in the norming phase is ignored. To express uncertainty due to norming, we propose a flexible method that is applicable in continuous norming and allows for a variety of score distributions, using Generalized Additive Models for Location, Scale, and Shape (GAMLSS; Rigby & Stasinopoulos, 2005). We assessed the performance of this method in a simulation study, by examining the quality of the resulting CIs. We varied the population model, procedure of estimating the CI, confidence level, sample size, value of the predictor, extremity of the test score, and type of variance-covariance matrix. The results showed that good quality of the CIs could be achieved in most conditions. The method is illustrated using normative data of the SON-R 6-40 test. We recommend test developers to use this approach to arrive at CIs, and thus properly express the uncertainty due to norm sampling fluctuations, in the context of continuous norming. Adopting this approach will help (e.g., clinical) practitioners to obtain a fair picture of the person assessed.

KW - CORRELATION MATRIX

U2 - 10.3758/s13428-018-1122-8

DO - 10.3758/s13428-018-1122-8

M3 - Article

C2 - 30402815

VL - 51

SP - 826

EP - 839

JO - Behavior Research Methods

JF - Behavior Research Methods

SN - 1554-351X

IS - 2

ER -

ID: 64310473