A Continuous Solution to the Norming Problem.
Conventional methods for producing test norms are often plagued with “jumps” or “gaps” (i.e., discontinuities) in norm tables and low confidence for assessing extreme scores. We propose a new approach for producing continuous test norms to address these problems that also has the added advantage of...
| Published in: | Assessment Vol. 25; no. 1; pp. 112 - 126 |
|---|---|
| Main Authors: | , , , |
| Format: | research tables/charts Journal Article |
| Published: |
Sage Publications Inc.
Jan2018
|
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=126378040&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 126378040 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10731911 G70 jtl: Assessment issn: 10731911 maglogo: Y pubinfo: dt: Jan2018 vid: 25 iid: 1 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 126378040 126378040 126378040 10.1177/1073191116656437 126378040 ppf: 112 ppct: 14 formats: tig: atl: A Continuous Solution to the Norming Problem. aug: au: Lenhard, Alexandra Lenhard, Wolfgang Suggate, Sebastian Segerer, Robin affil: Psychometrica, Institute for Psychological Diagnostics, Dettelbach, Bavaria, Germany sug: subj: Reference Values Sample Size Variable Data Analysis Bias (Research) ab: Conventional methods for producing test norms are often plagued with “jumps” or “gaps” (i.e., discontinuities) in norm tables and low confidence for assessing extreme scores. We propose a new approach for producing continuous test norms to address these problems that also has the added advantage of not requiring assumptions about the distribution of the raw data: Norm values are established from raw data by modeling the latter ones as a function of both percentile scores and an explanatory variable (e.g., age). The proposed method appears to minimize bias arising from sampling and measurement error, while handling marked deviations from normality—such as are commonplace in clinical samples. In addition to step-by-step instructions in how to apply this method, we demonstrate its advantages over conventional discrete norming procedures using norming data from two different psychometric tests, employing either age norms (N = 3,555) or grade norms (N = 1,400). pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|