Multiple IQ-Achievement Comparisons: Effects on Severe Discrepancy Determination

1992 ◽  
Vol 15 (3) ◽  
pp. 167-174 ◽  
Author(s):  
Larry D. Evans
Keyword(s):  
Learning Disability ◽  
Type I Error ◽  
Multiple Comparisons ◽  
Type I ◽  
Discrepancy Model ◽  
Learning Disability Identification ◽  
Severe Discrepancy ◽  
Disability Identification ◽  
Woodcock Johnson

Increased Type I error resulting from multiple IQ-achievement comparisons may inflate learning disability identification rates for discrepancy models. The magnitude of such inflation was investigated with 87 referred students given the WISC-R and Woodcock-Johnson (R) Tests of Achievement. Five IQ-achievement comparisons were made for each student. Correction for multiple comparisons significantly decreased the number of students and achievement areas found to demonstrate significant IQ-achievement differences. However, less dramatic decreases were found for students and achievement areas determined to show discrepancies. It was concluded that the magnitude of inflation is a function of number of comparisons, degree of correction for multiple comparisons, and discrepancy model used.

scholarly journals Sisvar: a Guide for its Bootstrap procedures in multiple comparisons

2014 ◽  
Vol 38 (2) ◽  
pp. 109-112 ◽  
Author(s):  
Daniel Furtado Ferreira
Keyword(s):  
Scientific Community ◽  
Type I Error ◽  
Multiple Comparisons ◽  
Error Rates ◽  
Type I ◽  
Type I Error Rates ◽  
Statistical Analysis System ◽  
Scientific Results ◽  
Analysis System ◽  
Multiple Comparison Procedures

Sisvar is a statistical analysis system with a large usage by the scientific community to produce statistical analyses and to produce scientific results and conclusions. The large use of the statistical procedures of Sisvar by the scientific community is due to it being accurate, precise, simple and robust. With many options of analysis, Sisvar has a not so largely used analysis that is the multiple comparison procedures using bootstrap approaches. This paper aims to review this subject and to show some advantages of using Sisvar to perform such analysis to compare treatments means. Tests like Dunnett, Tukey, Student-Newman-Keuls and Scott-Knott are performed alternatively by bootstrap methods and show greater power and better controls of experimentwise type I error rates under non-normal, asymmetric, platykurtic or leptokurtic distributions.

Psychiatric Research Series Editor: Wayne Hall: A Critical Survey of Scientific Methods in Two Psychiatry Journals

1987 ◽  
Vol 21 (3) ◽  
pp. 367-373 ◽  
Author(s):  
John Davies
Keyword(s):  
High Frequency ◽  
Type I Error ◽  
Multiple Comparisons ◽  
Psychiatric Research ◽  
Type I ◽  
Critical Survey ◽  
Psychiatry Training ◽  
Scientific Methods ◽  
Methodological Errors ◽  
Statistical Designs

In a critical review of 29 analytical papers from the 1985 Australian and New Zealand Journal of Psychiatry and the American Journal of Psychiatry, examples of 10 methodological errors were found. Twenty-three papers contained at least one error. The commonest error in design was the failure to assess outcome independently of knowledge of the subjects' groups. The most frequent error in analysis was the failure to control for the increased type I error rate when multiple comparisons were made. The high frequency of statistical errors in published articles indicates a need for research methodology to be included in postgraduate psychiatry training. The limitations of statistical designs highlight the importance of alternative investigative models in psychiatric research.

scholarly journals Counting Differently: Assessing Mathematics Achievement in Signing Deaf and Hard of Hearing Children Through a Unique Lens

2021 ◽  
Author(s):  
Jon Henner ◽  
Claudia Pagliaro ◽  
SaraBeth Sullivan ◽  
Robert Hoffmeister
Keyword(s):  
Mathematics Achievement ◽  
Learning Disability ◽  
Hard Of Hearing ◽  
Mathematics Performance ◽  
Hearing Status ◽  
Signed Language ◽  
Learning Disability Identification ◽  
Disability Identification ◽  
Hearing Children

Limited studies exist that connect using signed language with mathematics performance in deaf and hard of hearing children. Here we examine 257 participants and compare their results on the NWEA MAP to their results on an assessment of ASL skills. We found that better ASL skills tended to result in better MAP performance. These results are moderated by factors such as age, gender, parental hearing status, and learning disability identification.

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