Using Z and age-equivalent scores to address WISC-IV floor effects for children with intellectual disability

被引:13
作者
Toffalini, E. [1 ]
Buono, S. [2 ]
Zagaria, T. [2 ]
Calcagni, A. [3 ]
Cornoldi, C. [1 ]
机构
[1] Univ Padua, Dept Gen Psychol, Via Venezia 8, I-35131 Padua, Italy
[2] Oasi Res Inst IRCCS, Psychol Unit, Troina, Italy
[3] Univ Padua, Dept Dev Psychol & Socializat, Padua, Italy
关键词
floor effect; intellectual disability; intelligence; WISC-IV; WORKING-MEMORY; INTELLIGENCE; INDIVIDUALS; SPEED; IQ;
D O I
10.1111/jir.12589
中图分类号
G76 [特殊教育];
学科分类号
040109 ;
摘要
Background The Wechsler Intelligence Scale for Children - Fourth Edition often produces floor effects in individuals with intellectual disability. Calculating respondents' Z or age-equivalent scores has been claimed to remedy this problem. Method The present study applied these methods to the Wechsler Intelligence Scale for Children - Fourth Edition scores of 198 individuals diagnosed with intellectual disability. Confirmatory factor analysis and profile analysis were conducted using a Bayesian approach. Results The intelligence structure in intellectual disability resembled the one previously reported for typical development, suggesting configural but not metric invariance. When Z or age-equivalent scores (but not traditional scaled scores) were used, the average profile resembled the one previously reported for other neurodevelopmental disorders. Conclusions Both methods avoided any floor effects, generating similar but not identical profiles. Despite some practical and conceptual limitations, age-equivalent scores may be easier to interpret. This was true even for a subgroup of individuals with more severe disabilities (mean IQ < 43).
引用
收藏
页码:528 / 538
页数:11
相关论文
共 41 条
  • [1] [Anonymous], 2004, Essentials of Assessment with WISC-IV
  • [2] [Anonymous], 2008, The Clinical Psychology Forum
  • [3] [Anonymous], 2014, BAYESIAN DATA ANAL, DOI DOI 10.1007/S13398-014-0173-7.2
  • [4] brms: An R Package for Bayesian Multilevel Models Using Stan
    Buerkner, Paul-Christian
    [J]. JOURNAL OF STATISTICAL SOFTWARE, 2017, 80 (01): : 1 - 28
  • [5] AIC model selection and multimodel inference in behavioral ecology: some background, observations, and comparisons
    Burnham, Kenneth P.
    Anderson, David R.
    Huyvaert, Kathryn P.
    [J]. BEHAVIORAL ECOLOGY AND SOCIOBIOLOGY, 2011, 65 (01) : 23 - 35
  • [6] A dimension reduction technique for two-mode non-convex fuzzy data
    Calcagni, A.
    Lombardi, L.
    Pascali, E.
    [J]. SOFT COMPUTING, 2016, 20 (02) : 749 - 762
  • [7] Processing speed in children with clinical disorders
    Calhoun, SL
    Mayes, SD
    [J]. PSYCHOLOGY IN THE SCHOOLS, 2005, 42 (04) : 333 - 343
  • [8] Difficulties in working memory updating in individuals with intellectual disability
    Carretti, B.
    Belacchi, C.
    Cornoldi, C.
    [J]. JOURNAL OF INTELLECTUAL DISABILITY RESEARCH, 2010, 54 : 337 - 345
  • [9] Measurement invariance of WISC-IV across normative and clinical samples
    Chen, Hsinyi
    Zhu, Jianjun
    [J]. PERSONALITY AND INDIVIDUAL DIFFERENCES, 2012, 52 (02) : 161 - 166
  • [10] Intelligence and the differentiation hypothesis
    Deary, IJ
    Egan, V
    Gibson, GJ
    Austin, EJ
    Brand, CR
    Kellaghan, T
    [J]. INTELLIGENCE, 1996, 23 (02) : 105 - 132