Month: February 2024

The Structure of Well Designed Online IQ Tests

There are convenient ways researchers can collect IQ scores and correlate the observed scores with measures of self-reported health, socio-economic attainment, personality or political views. In platforms such as Prolific or MTurk, participants make money in their spare time by completing tasks. Designing a test that displays both a high loading on the general factor of intelligence, while avoiding measurement bias and bad quality data from online participants, is quite a challenging task.


  1. Introduction page content
  2. Item’s pass rate and g-loading
  3. Lazy and dishonest test takers
  4. Short versus long test
  5. Scrolling dilemma
  6. Item type “write-in”
  7. Instruction and rules
  8. Cultural content and cultural bias
  9. Computerized Ability Test

The issues related to online testing are illustrated based on the numerous IQ tests Jurij Fedorov devised, with my assistance, using Alchemer’s professional software.

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Gender wage gap: Why the discrimination theory (likely) fails

Probably the most rehearsed explanation of the gender pay gap is discrimination. After accounting for traditional labor market factors, a large residual gap remains. This residual gap is also called the unexplained gap. Researchers often commit the fallacy of equating unexplained effect to discrimination effect instead of omitted variable bias. In fact, most wage decomposition models are probably contaminated by bias. This article will explain that much of the residual gap is likely due to other causes. In particular, time flexibility. The evidence for the discrimination effect is often ambiguous.

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