PMID- 37929259
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20231107
IS  - 1552-3888 (Electronic)
IS  - 0013-1644 (Print)
IS  - 0013-1644 (Linking)
VI  - 81
IP  - 2
DP  - 2021 Apr
TI  - Improvement of Norm Score Quality via Regression-Based Continuous Norming.
PG  - 229-261
LID - 10.1177/0013164420928457 [doi]
AB  - The interpretation of psychometric test results is usually based on norm scores. 
      We compared semiparametric continuous norming (SPCN) with conventional norming 
      methods by simulating results for test scales with different item numbers and 
      difficulties via an item response theory approach. Subsequently, we modeled the 
      norm scores based on random samples with varying sizes either with a conventional 
      ranking procedure or SPCN. The norms were then cross-validated by using an 
      entirely representative sample of N = 840,000 for which different measures of 
      norming error were computed. This process was repeated 90,000 times. Both 
      approaches benefitted from an increase in sample size, with SPCN reaching optimal 
      results with much smaller samples. Conventional norming performed worse on data 
      fit, age-related errors, and number of missings in the norm tables. The data fit 
      in conventional norming of fixed subsample sizes varied with the granularity of 
      the age brackets, calling into question general recommendations for sample sizes 
      in test norming. We recommend that test norms should be based on statistical 
      models of the raw score distributions instead of simply compiling norm tables via 
      conventional ranking procedures.
CI  - (c) The Author(s) 2020.
FAU - Lenhard, Wolfgang
AU  - Lenhard W
AUID- ORCID: 0000-0002-8184-6889
AD  - University of Wuerzburg, Wuerzburg, Germany.
FAU - Lenhard, Alexandra
AU  - Lenhard A
AD  - Psychometrica, Dettelbach, Germany.
LA  - eng
PT  - Journal Article
DEP - 20200616
PL  - United States
TA  - Educ Psychol Meas
JT  - Educational and psychological measurement
JID - 0372767
PMC - PMC10621686
OTO - NOTNLM
OT  - continuous norming
OT  - curve fitting
OT  - data smoothing
OT  - inferential norming
OT  - percentile estimation
OT  - regression-based norming
COIS- The authors declared no potential conflicts of interest with respect to the 
      research, authorship, and/or publication of this article
EDAT- 2021/04/01 00:00
MHDA- 2021/04/01 00:01
PMCR- 2022/04/01
CRDT- 2023/11/06 04:50
PHST- 2021/04/01 00:01 [medline]
PHST- 2021/04/01 00:00 [pubmed]
PHST- 2023/11/06 04:50 [entrez]
PHST- 2022/04/01 00:00 [pmc-release]
AID - 10.1177_0013164420928457 [pii]
AID - 10.1177/0013164420928457 [doi]
PST - ppublish
SO  - Educ Psychol Meas. 2021 Apr;81(2):229-261. doi: 10.1177/0013164420928457. Epub 
      2020 Jun 16.