The Experts below are selected from a list of 210 Experts worldwide ranked by ideXlab platform
Olavo B Amaral - One of the best experts on this subject based on the ideXlab platform.
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effect Size and statistical power in the rodent fear conditioning literature a systematic review
PLOS ONE, 2018Co-Authors: Clarissa Franca Dias Carneiro, Thiago C Moulin, Malcolm R Macleod, Olavo B AmaralAbstract:Proposals to increase research reproducibility frequently call for focusing on effect Sizes instead of p values, as well as for increasing the statistical power of experiments. However, it is unclear to what extent these two concepts are indeed taken into account in basic biomedical science. To study this in a real-case scenario, we performed a systematic review of effect Sizes and statistical power in studies on learning of rodent fear conditioning, a widely used behavioral task to evaluate memory. Our search criteria yielded 410 experiments comparing control and treated groups in 122 articles. Interventions had a mean effect Size of 29.5%, and amnesia caused by memory-impairing interventions was nearly always partial. Mean statistical power to detect the average effect Size observed in well-powered experiments with significant differences (37.2%) was 65%, and was lower among studies with non-significant results. Only one article reported a Sample Size calculation, and our Estimated Sample Size to achieve 80% power considering typical effect Sizes and variances (15 animals per group) was reached in only 12.2% of experiments. Actual effect Sizes correlated with effect Size inferences made by readers on the basis of textual descriptions of results only when findings were non-significant, and neither effect Size nor power correlated with study quality indicators, number of citations or impact factor of the publishing journal. In summary, effect Sizes and statistical power have a wide distribution in the rodent fear conditioning literature, but do not seem to have a large influence on how results are described or cited. Failure to take these concepts into consideration might limit attempts to improve reproducibility in this field of science.
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effect Size and statistical power in the rodent fear conditioning literature a systematic review
bioRxiv, 2017Co-Authors: Clarissa Franca Dias Carneiro, Thiago C Moulin, Malcolm R Macleod, Olavo B AmaralAbstract:Proposals to increase research reproducibility frequently call for focusing on effect Sizes instead of p values, as well as for increasing the statistical power of experiments. However, it is unclear to what extent these two concepts are indeed taken into account in basic biomedical science. To study this in a real-case scenario, we performed a systematic review of effect Sizes and statistical power in studies using rodent fear conditioning, a widely used behavioral task to evaluate learning and memory. Our search criteria yielded 410 experiments comparing control and treated groups in 122 articles. Interventions with statistically significant differences had a mean effect Size of 45.6%, and amnesia caused by memory-impairing interventions was nearly always partial. Mean statistical power to detect the average effect Size observed in well-powered experiments (37.2%) was 65%, and was lower in studies with non-significant results. Only one article reported a Sample Size calculation, and our Estimated Sample Size to achieve 80% power considering typical effect Sizes and variances (15 animals per group) was reached in only 12.2% of experiments. Effect Size correlated with textual descriptions of results only when findings were non-significant, and neither effect Size nor power correlated with study quality indicators, number of citations or impact factor of articles. In summary, effect Sizes and statistical power have a wide distribution in the rodent fear conditioning literature, but do not seem to have a large influence on how results are described or cited. Failure to take these concepts into consideration might limit attempts to improve reproducibility in this field of science.
Rupam Tripura - One of the best experts on this subject based on the ideXlab platform.
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intracluster correlation coefficients in the greater mekong subregion for Sample Size calculations of cluster randomized malaria trials
Malaria Journal, 2019Co-Authors: Pimnara Peerawaranun, Jordi Landier, Francois Nosten, Thuynhien Nguyen, Tran Tinh Hien, Rupam TripuraAbstract:Sample Size calculations for cluster randomized trials are a recognized methodological challenge for malaria research in pre-elimination settings. Positively correlated responses from the participants in the same cluster are a key feature in the Estimated Sample Size required for a cluster randomized trial. The degree of correlation is measured by the intracluster correlation coefficient (ICC) where a higher coefficient suggests a closer correlation hence less heterogeneity within clusters but more heterogeneity between clusters. Data on uPCR-detected Plasmodium falciparum and Plasmodium vivax infections from a recent cluster randomized trial which aimed at interrupting malaria transmission through mass drug administrations were used to calculate the ICCs for prevalence and incidence of Plasmodium infections. The trial was conducted in four countries in the Greater Mekong Subregion, Laos, Myanmar, Vietnam and Cambodia. Exact and simulation approaches were used to estimate ICC values for both the prevalence and the incidence of parasitaemia. In addition, the latent variable approach to estimate ICCs for the prevalence was utilized. The ICCs for prevalence ranged between 0.001 and 0.082 for all countries. The ICC from the combined 16 villages in the Greater Mekong Subregion were 0.26 and 0.21 for P. falciparum and P. vivax respectively. The ICCs for incidence of parasitaemia ranged between 0.002 and 0.075 for Myanmar, Cambodia and Vietnam. There were very high ICCs for incidence in the range of 0.701 to 0.806 in Laos during follow-up. ICC estimates can help researchers when designing malaria cluster randomized trials. A high variability in ICCs and hence Sample Size requirements between study sites was observed. Realistic Sample Size estimates for cluster randomized malaria trials in the Greater Mekong Subregion have to assume high between cluster heterogeneity and ICCs. This work focused on uPCR-detected infections; there remains a need to develop more ICC references for trials designed around prevalence and incidence of clinical outcomes. Adequately powered trials are critical to estimate the benefit of interventions to malaria in a reliable and reproducible fashion. Trial registration: ClinicalTrials.govNCT01872702. Registered 7 June 2013. Retrospectively registered. https://clinicaltrials.gov/ct2/show/NCT01872702
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Intracluster correlation coefficients in the Greater Mekong Subregion for Sample Size calculations of cluster randomized malaria trials Malaria Journal
Malaria Journal, 2019Co-Authors: Pimnara Peerawaranun, Jordi Landier, Francois Nosten, Thuynhien Nguyen, Tran Tinh Hien, Rupam Tripura, Thomas J. Peto, Koukeo Phommasone, Mayfong Mayxay, Nicholas P. J. DayAbstract:Background: Sample Size calculations for cluster randomized trials are a recognized methodological challenge for malaria research in pre-elimination settings. Positively correlated responses from the participants in the same cluster are a key feature in the Estimated Sample Size required for a cluster randomized trial. The degree of correlation is measured by the intracluster correlation coefficient (ICC) where a higher coefficient suggests a closer correlation hence less heterogeneity within clusters but more heterogeneity between clusters. Methods: Data on uPCR-detected Plasmodium falciparum and Plasmodium vivax infections from a recent cluster randomized trial which aimed at interrupting malaria transmission through mass drug administrations were used to calculate the ICCs for prevalence and incidence of Plasmodium infections. The trial was conducted in four countries in the Greater Mekong Subregion, Laos, Myanmar, Vietnam and Cambodia. Exact and simulation approaches were used to estimate ICC values for both the prevalence and the incidence of parasitaemia. In addition, the latent variable approach to estimate ICCs for the prevalence was utilized. Results: The ICCs for prevalence ranged between 0.001 and 0.082 for all countries. The ICC from the combined 16 villages in the Greater Mekong Subregion were 0.26 and 0.21 for P. falciparum and P. vivax respectively. The ICCs for incidence of parasitaemia ranged between 0.002 and 0.075 for Myanmar, Cambodia and Vietnam. There were very high ICCs for incidence in the range of 0.701 to 0.806 in Laos during follow-up. Conclusion: ICC estimates can help researchers when designing malaria cluster randomized trials. A high variability in ICCs and hence Sample Size requirements between study sites was observed. Realistic Sample Size estimates for cluster randomized malaria trials in the Greater Mekong Subregion have to assume high between cluster heterogene-ity and ICCs. This work focused on uPCR-detected infections; there remains a need to develop more ICC references © The Author(s) 2019. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article' s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article
Clarissa Franca Dias Carneiro - One of the best experts on this subject based on the ideXlab platform.
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effect Size and statistical power in the rodent fear conditioning literature a systematic review
PLOS ONE, 2018Co-Authors: Clarissa Franca Dias Carneiro, Thiago C Moulin, Malcolm R Macleod, Olavo B AmaralAbstract:Proposals to increase research reproducibility frequently call for focusing on effect Sizes instead of p values, as well as for increasing the statistical power of experiments. However, it is unclear to what extent these two concepts are indeed taken into account in basic biomedical science. To study this in a real-case scenario, we performed a systematic review of effect Sizes and statistical power in studies on learning of rodent fear conditioning, a widely used behavioral task to evaluate memory. Our search criteria yielded 410 experiments comparing control and treated groups in 122 articles. Interventions had a mean effect Size of 29.5%, and amnesia caused by memory-impairing interventions was nearly always partial. Mean statistical power to detect the average effect Size observed in well-powered experiments with significant differences (37.2%) was 65%, and was lower among studies with non-significant results. Only one article reported a Sample Size calculation, and our Estimated Sample Size to achieve 80% power considering typical effect Sizes and variances (15 animals per group) was reached in only 12.2% of experiments. Actual effect Sizes correlated with effect Size inferences made by readers on the basis of textual descriptions of results only when findings were non-significant, and neither effect Size nor power correlated with study quality indicators, number of citations or impact factor of the publishing journal. In summary, effect Sizes and statistical power have a wide distribution in the rodent fear conditioning literature, but do not seem to have a large influence on how results are described or cited. Failure to take these concepts into consideration might limit attempts to improve reproducibility in this field of science.
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effect Size and statistical power in the rodent fear conditioning literature a systematic review
bioRxiv, 2017Co-Authors: Clarissa Franca Dias Carneiro, Thiago C Moulin, Malcolm R Macleod, Olavo B AmaralAbstract:Proposals to increase research reproducibility frequently call for focusing on effect Sizes instead of p values, as well as for increasing the statistical power of experiments. However, it is unclear to what extent these two concepts are indeed taken into account in basic biomedical science. To study this in a real-case scenario, we performed a systematic review of effect Sizes and statistical power in studies using rodent fear conditioning, a widely used behavioral task to evaluate learning and memory. Our search criteria yielded 410 experiments comparing control and treated groups in 122 articles. Interventions with statistically significant differences had a mean effect Size of 45.6%, and amnesia caused by memory-impairing interventions was nearly always partial. Mean statistical power to detect the average effect Size observed in well-powered experiments (37.2%) was 65%, and was lower in studies with non-significant results. Only one article reported a Sample Size calculation, and our Estimated Sample Size to achieve 80% power considering typical effect Sizes and variances (15 animals per group) was reached in only 12.2% of experiments. Effect Size correlated with textual descriptions of results only when findings were non-significant, and neither effect Size nor power correlated with study quality indicators, number of citations or impact factor of articles. In summary, effect Sizes and statistical power have a wide distribution in the rodent fear conditioning literature, but do not seem to have a large influence on how results are described or cited. Failure to take these concepts into consideration might limit attempts to improve reproducibility in this field of science.
Thiago C Moulin - One of the best experts on this subject based on the ideXlab platform.
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effect Size and statistical power in the rodent fear conditioning literature a systematic review
PLOS ONE, 2018Co-Authors: Clarissa Franca Dias Carneiro, Thiago C Moulin, Malcolm R Macleod, Olavo B AmaralAbstract:Proposals to increase research reproducibility frequently call for focusing on effect Sizes instead of p values, as well as for increasing the statistical power of experiments. However, it is unclear to what extent these two concepts are indeed taken into account in basic biomedical science. To study this in a real-case scenario, we performed a systematic review of effect Sizes and statistical power in studies on learning of rodent fear conditioning, a widely used behavioral task to evaluate memory. Our search criteria yielded 410 experiments comparing control and treated groups in 122 articles. Interventions had a mean effect Size of 29.5%, and amnesia caused by memory-impairing interventions was nearly always partial. Mean statistical power to detect the average effect Size observed in well-powered experiments with significant differences (37.2%) was 65%, and was lower among studies with non-significant results. Only one article reported a Sample Size calculation, and our Estimated Sample Size to achieve 80% power considering typical effect Sizes and variances (15 animals per group) was reached in only 12.2% of experiments. Actual effect Sizes correlated with effect Size inferences made by readers on the basis of textual descriptions of results only when findings were non-significant, and neither effect Size nor power correlated with study quality indicators, number of citations or impact factor of the publishing journal. In summary, effect Sizes and statistical power have a wide distribution in the rodent fear conditioning literature, but do not seem to have a large influence on how results are described or cited. Failure to take these concepts into consideration might limit attempts to improve reproducibility in this field of science.
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effect Size and statistical power in the rodent fear conditioning literature a systematic review
bioRxiv, 2017Co-Authors: Clarissa Franca Dias Carneiro, Thiago C Moulin, Malcolm R Macleod, Olavo B AmaralAbstract:Proposals to increase research reproducibility frequently call for focusing on effect Sizes instead of p values, as well as for increasing the statistical power of experiments. However, it is unclear to what extent these two concepts are indeed taken into account in basic biomedical science. To study this in a real-case scenario, we performed a systematic review of effect Sizes and statistical power in studies using rodent fear conditioning, a widely used behavioral task to evaluate learning and memory. Our search criteria yielded 410 experiments comparing control and treated groups in 122 articles. Interventions with statistically significant differences had a mean effect Size of 45.6%, and amnesia caused by memory-impairing interventions was nearly always partial. Mean statistical power to detect the average effect Size observed in well-powered experiments (37.2%) was 65%, and was lower in studies with non-significant results. Only one article reported a Sample Size calculation, and our Estimated Sample Size to achieve 80% power considering typical effect Sizes and variances (15 animals per group) was reached in only 12.2% of experiments. Effect Size correlated with textual descriptions of results only when findings were non-significant, and neither effect Size nor power correlated with study quality indicators, number of citations or impact factor of articles. In summary, effect Sizes and statistical power have a wide distribution in the rodent fear conditioning literature, but do not seem to have a large influence on how results are described or cited. Failure to take these concepts into consideration might limit attempts to improve reproducibility in this field of science.
Malcolm R Macleod - One of the best experts on this subject based on the ideXlab platform.
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effect Size and statistical power in the rodent fear conditioning literature a systematic review
PLOS ONE, 2018Co-Authors: Clarissa Franca Dias Carneiro, Thiago C Moulin, Malcolm R Macleod, Olavo B AmaralAbstract:Proposals to increase research reproducibility frequently call for focusing on effect Sizes instead of p values, as well as for increasing the statistical power of experiments. However, it is unclear to what extent these two concepts are indeed taken into account in basic biomedical science. To study this in a real-case scenario, we performed a systematic review of effect Sizes and statistical power in studies on learning of rodent fear conditioning, a widely used behavioral task to evaluate memory. Our search criteria yielded 410 experiments comparing control and treated groups in 122 articles. Interventions had a mean effect Size of 29.5%, and amnesia caused by memory-impairing interventions was nearly always partial. Mean statistical power to detect the average effect Size observed in well-powered experiments with significant differences (37.2%) was 65%, and was lower among studies with non-significant results. Only one article reported a Sample Size calculation, and our Estimated Sample Size to achieve 80% power considering typical effect Sizes and variances (15 animals per group) was reached in only 12.2% of experiments. Actual effect Sizes correlated with effect Size inferences made by readers on the basis of textual descriptions of results only when findings were non-significant, and neither effect Size nor power correlated with study quality indicators, number of citations or impact factor of the publishing journal. In summary, effect Sizes and statistical power have a wide distribution in the rodent fear conditioning literature, but do not seem to have a large influence on how results are described or cited. Failure to take these concepts into consideration might limit attempts to improve reproducibility in this field of science.
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effect Size and statistical power in the rodent fear conditioning literature a systematic review
bioRxiv, 2017Co-Authors: Clarissa Franca Dias Carneiro, Thiago C Moulin, Malcolm R Macleod, Olavo B AmaralAbstract:Proposals to increase research reproducibility frequently call for focusing on effect Sizes instead of p values, as well as for increasing the statistical power of experiments. However, it is unclear to what extent these two concepts are indeed taken into account in basic biomedical science. To study this in a real-case scenario, we performed a systematic review of effect Sizes and statistical power in studies using rodent fear conditioning, a widely used behavioral task to evaluate learning and memory. Our search criteria yielded 410 experiments comparing control and treated groups in 122 articles. Interventions with statistically significant differences had a mean effect Size of 45.6%, and amnesia caused by memory-impairing interventions was nearly always partial. Mean statistical power to detect the average effect Size observed in well-powered experiments (37.2%) was 65%, and was lower in studies with non-significant results. Only one article reported a Sample Size calculation, and our Estimated Sample Size to achieve 80% power considering typical effect Sizes and variances (15 animals per group) was reached in only 12.2% of experiments. Effect Size correlated with textual descriptions of results only when findings were non-significant, and neither effect Size nor power correlated with study quality indicators, number of citations or impact factor of articles. In summary, effect Sizes and statistical power have a wide distribution in the rodent fear conditioning literature, but do not seem to have a large influence on how results are described or cited. Failure to take these concepts into consideration might limit attempts to improve reproducibility in this field of science.