Multiple Trials May Yield Exaggerated Effect Size Estimates

@article{Brand2011MultipleTM,
  title={Multiple Trials May Yield Exaggerated Effect Size Estimates},
  author={Andrew Brand and Michael T. Bradley and Lisa A. Best and George Valentin Stoica},
  journal={The Journal of General Psychology},
  year={2011},
  volume={138},
  pages={1 - 11}
}
ABSTRACT Published psychological research attempting to support the existence of small and medium effect sizes may not have enough participants to do so accurately, and thus, repeated trials or the use of multiple items may be used in an attempt to obtain significance. Through a series of Monte-Carlo simulations, this article describes the results of multiple trials or items on effect size estimates when the averages and aggregates of a dependent measure are analyzed. The simulations revealed a… 
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28 Citations
Background Citations
6
Methods Citations
2

28 Citations

Citation Type

Citation Type

Accuracy of Effect Size Estimates From Published Psychological Experiments Involving Multiple Trials
TLDR
Simulations showed a large increase in observed effect size averages and the power to accept these estimates as statistically significant increased over numbers of trials or items.
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It is concluded that, in practice, d ′ c together with plausible estimates of inter-trial correlation will produce a more precise effect size range compared to that suggested by Brand and colleagues (2011).
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It was evident that sample sizes for most psychological studies are adequate for large effect sizes defined at .8, and it was perhaps doubtful if these ideal levels of alpha and power have generally been achieved for medium effect sizes in actual research, since 170 participants would be required.
Effect Size Overview Population and Sample Effect Sizes
  • Psychology
In statistics, an effect size is a measure of the strength of the relationship between two variables in a statistical population, or a sample-based estimate of that quantity. An effect size…
Interpreting Effect Size Estimates through Graphic Analysis of Raw Data Distributions
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This paper considers and simulate cases where graphical analyses reveal distortion in effect size estimates, and highlights the value of graphing data to interpret effect size Estimates.
The Precision of Effect Size Estimation From Published Psychological Research
TLDR
Additional exploratory analyses revealed that CI widths varied across psychological research areas and thatCI widths were not discernably decreasing over time, and the theoretical implications are discussed along with ways of reducing the CI widthS and thus improving precision of effect size estimation.
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A Monte-Carlo simulation was conducted to assess the extent that a correlation estimate can be inflated when an average-based measure is used in a commonly employed correlational design and reveals that the inflation of the correlation estimateCan be substantial, up to 76%.
What Can Cross-Cultural Correlations Teach Us about Human Nature?
TLDR
This work provides examples of how cross-cultural non-equivalence of measurement gives rise to problems in the context of testing evolutionary hypotheses about human behavior, and offers some suggestions for future research.
Examining Treatment Effects for Single-Case ABAB Designs through Sensitivity Analyses
TLDR
This work performed a series of sensitivity analyses while also exploring ways in which HLM can be used to examine new and different questions when dealing with published single-case data.
Using PPT to account for randomness in perception
TLDR
Most participants in both experiments tended to perform at a less-than-perfect level, even after their scores were corrected, demonstrating that at least one systematic factor influences detection that is not included in signal detection theory.
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