Bonferroni, Holm, and Hochberg Corrections: Fun Names, Serious Changes to <i>P</i> Values

McLaughlin, Matthew; Sainani, Kristin L.

doi:10.1016/j.pmrj.2014.04.006

Cited by 75 publications

(58 citation statements)

References 4 publications

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“…We excluded variants of unknown significance and we did not count the index aberration in the total number. We found that a total of 105 of 271 (38.7%) are significant at P≤.05; using the Bonferroni correction 32 for multiple comparisons, a total of 31 of 271 (11.4%) are significant at P≤.00,018.…”

Section: Molecular Landscape Of Patients With Gna* Alterationsmentioning

confidence: 77%

GNAS, GNAQ,andGNA11alterations in patients with diverse cancers

Parish

Nguyen

Goodman

et al. 2018

Cancer

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Section: Molecular Landscape Of Patients With Gna* Alterationsmentioning

confidence: 77%

GNAS, GNAQ,andGNA11alterations in patients with diverse cancers

Parish

Nguyen

Goodman

et al. 2018

Cancer

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“…This usually arises when the same statistical tests are repeatedly computed from the same set of observations in a hypothesis-driven research [33]. Fortunately, there are several ways of addressing this issue, many of which require researchers to set a more stringent significance threshold [34,35]. For example, while many of the transition correlations presented in the current study remained significant at P <.01, it is important to note that we did not have a priori hypotheses regarding what specific types of location pairs would be most relevant.…”

Section: Discussionmentioning

confidence: 99%

Predicting Social Anxiety From Global Positioning System Traces of College Students: Feasibility Study

et al. 2018

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BackgroundSocial anxiety is highly prevalent among college students. Current methodologies for detecting symptoms are based on client self-report in traditional clinical settings. Self-report is subject to recall bias, while visiting a clinic requires a high level of motivation. Assessment methods that use passively collected data hold promise for detecting social anxiety symptoms and supplementing self-report measures. Continuously collected location data may provide a fine-grained and ecologically valid way to assess social anxiety in situ.ObjectiveThe objective of our study was to examine the feasibility of leveraging noninvasive mobile sensing technology to passively assess college students’ social anxiety levels. Specifically, we explored the different relationships between mobility and social anxiety to build a predictive model that assessed social anxiety from passively generated Global Positioning System (GPS) data.MethodsWe recruited 228 undergraduate participants from a Southeast American university. Social anxiety symptoms were assessed using self-report instruments at a baseline laboratory session. An app installed on participants’ personal mobile phones passively sensed data from the GPS sensor for 2 weeks. The proposed framework supports longitudinal, dynamic tracking of college students to evaluate the relationship between their social anxiety and movement patterns in the college campus environment. We first extracted the following mobility features: (1) cumulative staying time at each different location, (2) the distribution of visits over time, (3) the entropy of locations, and (4) the frequency of transitions between locations. Next, we studied the correlation between these features and participants’ social anxiety scores to enhance the understanding of how students’ social anxiety levels are associated with their mobility. Finally, we used a neural network-based prediction method to predict social anxiety symptoms from the extracted daily mobility features.ResultsSeveral mobility features correlated with social anxiety levels. Location entropy was negatively associated with social anxiety (during weekdays, r=−0.67; and during weekends, r=−0.51). More (vs less) socially anxious students were found to avoid public areas and engage in less leisure activities during evenings and weekends, choosing instead to spend more time at home after school (4 pm-12 am). Our prediction method based on extracted mobility features from GPS trajectories successfully classified participants as high or low socially anxious with an accuracy of 85% and predicted their social anxiety score (on a scale of 0-80) with a root-mean-square error of 7.06.ConclusionsResults indicate that extracting and analyzing mobility features may help to reveal how social anxiety symptoms manifest in the daily lives of college students. Given the ubiquity of mobile phones in our society, understanding how to leverage passively sensed data has strong potential to address the growing needs for mental health monitoring and treatment.

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“…The other data are presented as mean ± SEM. Subsequently, we performed the Benjamini-Hochberg test to correct the p-value of every parameter for multiple hypothesis testing (Benjamini & Hochberg, 1995;McLaughlin & Sainani, 2014). These corrections are shown in Table 1.…”

Section: Discussionmentioning

confidence: 99%

Impairment of motor but not anxiety‐like behavior caused by the increase of dopamine during development is sustained in zebrafish larvae at later stages

Lima

Alvarenga

Codo

et al. 2020

Intl J of Devlp Neuroscience

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Many neuropsychiatric disorders are associated with both dopaminergic (DAergic) and developmental hypotheses. Since DAergic receptors are expressed in the developing brain, it is possible that alterations in dopamine (DA) signaling may impair brain development and consequent behavior. In our previous study, using a zebrafish model, we showed that an increase of DA during the 3 to 5 days postfertilization (dpf) developmental window (an important window for GABAergic neuronal differentiation) affects the motor behavior of 5 dpf larvae. In this study, we set out to determine whether these behavioral alterations were sustained in larvae at older stages (7 and 14 dpf). To test this hypothesis, we chronically treated zebrafish larvae from 3 to 5 dpf with DA. After washing the drug, we recorded and analyzed the first 5 and 30 min of the motor behavior of 5, 7, and 14 dpf subjects. We analyzed mobile episodes, distance traveled, time mobile, distance traveled per mobile episode, time in movement per mobile episode, and distance traveled per time mobile. We showed, once again, that an increase of DA during the 3 to 5 dpf developmental window reduces the number of movement episodes initiated by 5 dpf larvae. We also detected a decrease of other motor behavior parameters in 5 dpf DA‐treated larvae. We observed that these alterations are sustained in the 7 dpf larvae. However, we did not see these general locomotor alterations in the 14 dpf larvae. Moreover, we detected a decrease of distance traveled and an increase of time of locomotion per episode in the first 5 min of behavioral analyses in 14 dpf DA‐treated larvae. To test if the alterations in the first 5 min were due to anxiety‐like behavior, we used a light/dark preference paradigm. We recorded 5dpf, 7dpf, and 14dpf larvae for 5 min and analyzed time of freezing, preference for light or dark, number of entries to the dark, percentage of time in the light. We observed that 5dpf larvae treated with DA showed more freezing, less passages to the dark, and more time spent in the light as compared to their control counterparts. But 7dpf and 14dpf larvae did not show these alterations. Taken overall, therefore, our results suggest that DA does play a role in the development of zebrafish motor behavior, and, furthermore, that some behaviors are more sensitive than others to the effects of DAergic imbalances during development.

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Bonferroni, Holm, and Hochberg Corrections: Fun Names, Serious Changes to P Values

Cited by 75 publications

References 4 publications

GNAS, GNAQ,andGNA11alterations in patients with diverse cancers

GNAS, GNAQ,andGNA11alterations in patients with diverse cancers

Predicting Social Anxiety From Global Positioning System Traces of College Students: Feasibility Study

Impairment of motor but not anxiety‐like behavior caused by the increase of dopamine during development is sustained in zebrafish larvae at later stages

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