Preprint

Norming of IQ tests on a ratio scale

This article is a preprint and has not been certified by peer review [What does this mean?].

Author(s) / Creator(s)

Melão junior, Hindemburg

Abstract / Description

In this article, we present a solution to one of the central problems of psychometrics over the past 100 years: a method for norming cognitive tests by producing scores on a ratio scale. This new approach is accompanied by many other complementary solutions, including the ability to accurately determine consistent values for the test ceilings, even when the theoretical rarity level at the top is much larger than the sample size. For example, in a sample of 3,000 subjects from a non-selective population, we can accurately determine the ceiling at the rarity level of 1 in 3 million by grouping the lower scores to compose a metric that allows us to estimate the higher scores while preserving the scale’s internal consistency. The higher the ceiling and the more difficult it is to norm using traditional methods, the greater the benefits of this method. In a non-selective sample of 50,000 people, we can determine the ceiling down to the level of 1 in 1 billion. Alternatively, with a sample of only a few hundred people with significantly above-average IQs, heavily biased by self-selection, we were able to determine the ceiling down to the level of 1 in a few billion even without knowing the parameters of this sample’s distribution. In samples severely contaminated by self-selection, we were able to neutralize this effect naturally, without the need for epicycle. We corrected for distortions in the dense tails and obtained a series of other advantages compared to traditional methods based on IRT and TCT [10], in addition to combining all the typical conceptual advantages inherent in ratio scales. We also opened the possibility of measuring animal and artificial intelligence on the same scale as human intelligence, among other possibilities yet to be discovered. We call this new procedure the “HM Method”.

Keyword(s)

HM Method ratio scale Elo system Thurstone Rasch model Birnbaum model Lord model Item Response Theory IRT Sigma Test Extended Sigma Test Titan Test Mega Test IQ Test WAIS Stanford—Binet 1PL 2PL 3PL 5PL pIQ rIQ Cognitive Ability Game Quantitative Methods Cognitive Skills Genius Diagnostic High Ability Artificial Intelligence Intelligence Measurement Artificial General Intelligence (AGI) LLM Benchmarking Neural Scaling Emergent Abilities Foundational Models Cognitive Architectures Animal Intelligence

Persistent Identifier

Date of first publication

2025-12-15

Publisher

PsychArchives

Citation

  • Author(s) / Creator(s)
    Melão junior, Hindemburg
  • PsychArchives acquisition timestamp
    2025-12-15T15:29:24Z
  • Made available on
    2025-12-15T15:29:24Z
  • Date of first publication
    2025-12-15
  • Abstract / Description
    In this article, we present a solution to one of the central problems of psychometrics over the past 100 years: a method for norming cognitive tests by producing scores on a ratio scale. This new approach is accompanied by many other complementary solutions, including the ability to accurately determine consistent values for the test ceilings, even when the theoretical rarity level at the top is much larger than the sample size. For example, in a sample of 3,000 subjects from a non-selective population, we can accurately determine the ceiling at the rarity level of 1 in 3 million by grouping the lower scores to compose a metric that allows us to estimate the higher scores while preserving the scale’s internal consistency. The higher the ceiling and the more difficult it is to norm using traditional methods, the greater the benefits of this method. In a non-selective sample of 50,000 people, we can determine the ceiling down to the level of 1 in 1 billion. Alternatively, with a sample of only a few hundred people with significantly above-average IQs, heavily biased by self-selection, we were able to determine the ceiling down to the level of 1 in a few billion even without knowing the parameters of this sample’s distribution. In samples severely contaminated by self-selection, we were able to neutralize this effect naturally, without the need for epicycle. We corrected for distortions in the dense tails and obtained a series of other advantages compared to traditional methods based on IRT and TCT [10], in addition to combining all the typical conceptual advantages inherent in ratio scales. We also opened the possibility of measuring animal and artificial intelligence on the same scale as human intelligence, among other possibilities yet to be discovered. We call this new procedure the “HM Method”.
    en
  • Publication status
    other
  • Review status
    notReviewed
  • Persistent Identifier
    https://hdl.handle.net/20.500.12034/16900
  • Persistent Identifier
    https://doi.org/10.23668/psycharchives.21511
  • Language of content
    eng
  • Publisher
    PsychArchives
  • Keyword(s)
    HM Method
  • Keyword(s)
    ratio scale
  • Keyword(s)
    Elo system
  • Keyword(s)
    Thurstone
  • Keyword(s)
    Rasch model
  • Keyword(s)
    Birnbaum model
  • Keyword(s)
    Lord model
  • Keyword(s)
    Item Response Theory
  • Keyword(s)
    IRT
  • Keyword(s)
    Sigma Test Extended
  • Keyword(s)
    Sigma Test
  • Keyword(s)
    Titan Test
  • Keyword(s)
    Mega Test
  • Keyword(s)
    IQ Test
  • Keyword(s)
    WAIS
  • Keyword(s)
    Stanford—Binet
  • Keyword(s)
    1PL
  • Keyword(s)
    2PL
  • Keyword(s)
    3PL
  • Keyword(s)
    5PL
  • Keyword(s)
    pIQ
  • Keyword(s)
    rIQ
  • Keyword(s)
    Cognitive Ability
  • Keyword(s)
    Game Quantitative Methods
  • Keyword(s)
    Cognitive Skills
  • Keyword(s)
    Genius Diagnostic
  • Keyword(s)
    High Ability
  • Keyword(s)
    Artificial Intelligence
  • Keyword(s)
    Intelligence Measurement
  • Keyword(s)
    Artificial General Intelligence (AGI)
  • Keyword(s)
    LLM Benchmarking
  • Keyword(s)
    Neural Scaling
  • Keyword(s)
    Emergent Abilities
  • Keyword(s)
    Foundational Models
  • Keyword(s)
    Cognitive Architectures
  • Keyword(s)
    Animal Intelligence
  • Dewey Decimal Classification number(s)
    150
  • Title
    Norming of IQ tests on a ratio scale
    en
  • DRO type
    preprint