| Author | Abramov, Dimitri Marques | |
| Author | Sá, Antonio Mauricio F. L. Miranda de | |
| Access date | 2021-04-26T20:06:28Z | |
| Available date | 2021-04-26T20:06:28Z | |
| Document date | 2021 | |
| Citation | ABRAMOV, Dimitri Marques; SÁ, Antonio Mauricio F. L. Miranda de. Probability waves: Adaptive cluster-based correction by convolution of p-value series from mass univariate analysis. Journal of Neuroscience Methods, v. 357, p. 1-8, Mar 26 2021. | pt_BR |
| ISSN | 0165-0270 | pt_BR |
| URI | https://www.arca.fiocruz.br/handle/icict/46920 | |
| Language | eng | pt_BR |
| Publisher | Elsevier [Commercial Publisher] | pt_BR |
| Rights | restricted access | |
| Title | Probability waves: Adaptive cluster-based correction by convolution of p-value series from mass univariate analysis | pt_BR |
| Type | Article | |
| DOI | 10.1016/j.jneumeth.2021.109155 | |
| Abstract | Background: Methods for p-value correction are criticized for either increasing Type II error or improperly reducing Type I error in large exploratory data analysis. This text considers patterns in probability vectors resulting from mass univariate analysis to correct p-values, where clusters of significant p-values may indicate true H0 rejection.
New method: We used ERP experimental data from control and ADHD boys to test the method. The Log10 of p-vector was convolved with a Gaussian window whose length was set as the shortest lag above which autocorrelation of each ERP wave may be assumed to have vanished. We realized Monte-Carlo simulations (MC) to (1) evaluate confidence intervals of rejected and non-rejected areas of our data, (2) to evaluate differences between corrected and uncorrected p-vectors or simulated ones in terms of distribution of significant p-values, and (3) to empirically verify the type-I error rate (comparing 10,000 pairs of mixed samples whit control and ADHD subjects).
Results: The differences between simulation or raw p-vector and corrected p-vectors were, respectively, minimal and maximal for window length set by autocorrelation in p-vector convolution.
Comparison with existing methods: Our method was less conservative while FDR methods rejected basically all significant p-values.The MC simulations presented 2.78 ± 4.83% of difference (20 channels) from corrected p-vector, while difference from raw p-vector was 596 ± 5.00% (p = 0.0003).
Conclusion: As a cluster-based correction, the present new method seems to be biological and statistically suitable to correct p-values in mass univariate analysis of ERP waves, which adopts adaptive parameters to correction. | pt_BR |
| Affilliation | Fundação Oswaldo Cruz. Instituto Nacional de Saúde da Mulher, da Criança e do Adolescente Fernandes Figueira. Rio de Janeiro, RJ, Brasil. | pt_BR |
| Affilliation | Universidade Federal do Rio de Janeiro. COPPE. Rio de Janeiro, RJ, Brasil. | pt_BR |
| Subject | Type-II error | pt_BR |
| Subject | Multiple comparisons | pt_BR |
| Subject | Mass univariate analysis | pt_BR |
| Subject | False discovery rate | pt_BR |
| Subject | Cluster-based statistics | pt_BR |
| Subject | Convolution | pt_BR |
| Embargo date | 2023-01-01 | |
