In many statistical applications that concern mathematical psychologists, the concept of Fisher i... more In many statistical applications that concern mathematical psychologists, the concept of Fisher information plays an important role. In this tutorial we clarify the concept of Fisher information as it manifests itself across three different statistical paradigms. First, in the frequentist paradigm, Fisher information is used to construct hypothesis tests and confidence intervals using maximum likelihood estimators; second, in the Bayesian paradigm, Fisher information is used to define a default prior; lastly, in the minimum description length paradigm, Fisher information is used to measure model complexity.
We describe a general method that allows experimenters to quantify the evidence from the data of ... more We describe a general method that allows experimenters to quantify the evidence from the data of a direct replication attempt given data already acquired from an original study. These so-called replication Bayes factors are a reconceptualization of the ones introduced by Verhagen and Wagenmakers (Journal of Experimental Psychology: General, 143(4), 1457-1475 2014) for the common t test. This reconceptualization is computationally simpler and generalizes easily to most common experimental designs for which Bayes factors are available. Keywords Evidence synthesis • Hypothesis testing • Meta-analysis • Replication The past 5 years have witnessed a dramatic increase in interest for replication studies, largely in response to psychology's "crisis of confidence" (e.g., Pashler & Wagenmakers, 2012). While this crisis is not unique to the field of psychology by any means, psychologists have been at the forefront of efforts to assess and improve reproducibility in science by way of large-scale replication initiatives, such as the Reproducibility Project: Psychology (Open Science Collaboration, 2015), the Social Psychology special issue on replication (Nosek & Lakens, 2014), and the various ManyLabs efforts (Ebersole et al., 2016; Klein et al., 2014). Although the importance of direct replication has been contested by some (for an overview of the most common arguments see Zwaan, Etz, Lucas, & Donnellan, 2017), the increasing prominence of replication studies has prompted researchers to examine the question of how to assess, statistically, the degree to which a replication study succeeds or fails.
The New England journal of statistics in data science, 2024
We introduce the anytime-valid (AV) logrank test, a version of the logrank test that provides typ... more We introduce the anytime-valid (AV) logrank test, a version of the logrank test that provides type-I error guarantees under optional stopping and optional continuation. The test is sequential without the need to specify a maximum sample size or stopping rule, and allows for cumulative meta-analysis with type-I error control. The method can be extended to define anytime-valid confidence intervals. The logrank test is an instance of the martingale tests based on E-variables that have been recently developed. We demonstrate type-I error guarantees for the test in a semiparametric setting of proportional hazards, show explicitly how to extend it to ties and confidence sequences and indicate further extensions to the full Cox regression model. Using a Gaussian approximation on the logrank statistic, we show that the AV logrank test (which itself is always exact) has a similar rejection region to O'Brien-Fleming α-spending but with the potential to achieve 100% power by optional continuation. Although our approach to study design requires a larger sample size, the expected sample size is competitive by optional stopping.
Bayesian inference for rank-order problems is frustrated by the absence of an explicit likelihood... more Bayesian inference for rank-order problems is frustrated by the absence of an explicit likelihood function. This hurdle can be overcome by assuming a latent normal representation that is consistent with the ordinal information in the data: the observed ranks are conceptualized as an impoverished reflection of an underlying continuous scale, and inference concerns the parameters that govern the latent representation. We apply this generic data-augmentation method to obtain Bayes factors for three popular rank-based tests: the rank sum test, the signed rank test, and Spearman's ρ s .
Archive for History of Exact Sciences, May 30, 2023
This Editorial reports an exchange in form of a comment and reply on the article "History and Nat... more This Editorial reports an exchange in form of a comment and reply on the article "History and Nature of the Jeffreys-Lindley Paradox" (Arch Hist Exact Sci 77:25, 2023) by Eric-Jan Wagenmakers and Alexander Ly. 1 Comments by J. Gray, Editor-in-Chief AHES does not normally publish correspondence about an article, and would prefer to see scholarly disagreements dealt with in the form of subsequent articles. We are making an exception in this case because of the significant difficulties involved in the interpretation and mathematical formulation of the Jeffreys-Lindley paradox, and the way they affect historical interpretations. 2 Comment on "History and nature of the Jeffreys-Lindley paradox" by J. L. Cherry (Joshua L. Cherry is a US government employee his comment cannot be copyrighted) The Jeffreys-Lindley paradox involves disagreements between classical and Bayesian null hypothesis tests applied to the same observations. The two approaches can lead to opposite conclusions: the classicalp-value may be low enough that the null hypothesis would be rejected while the Bayesian posterior probability favors the null. The paradox, according to Lindley (1957), is that whatever the prior probability of B Jeremy Gray
Hypotheses concerning the distribution of multinomial proportions typically entail exact equality... more Hypotheses concerning the distribution of multinomial proportions typically entail exact equality constraints that can be evaluated using standard tests. Whenever researchers formulate inequality constrained hypotheses, however, they must rely on sampling-based methods that are relatively inefficient and computationally expensive. To address this problem we developed a bridge sampling routine that allows an efficient evaluation of multinomial inequality constraints. An empirical application showcases that bridge sampling outperforms current Bayesian methods, especially when relatively little posterior mass falls in the restricted parameter space. The method is extended to mixtures between equality and inequality constrained hypotheses.
RationaleSubstance use peaks during the developmental period known as emerging adulthood (ages 18... more RationaleSubstance use peaks during the developmental period known as emerging adulthood (ages 18–25), but not every individual who uses substances during this period engages in frequent or problematic use. Although individual differences in neurocognition appear to predict use severity, mechanistic neurocognitive risk factors with clear links to both behavior and neural circuitry have yet to be identified. Here, we aim to do so with an approach rooted in computational psychiatry, an emerging field in which formal models are used to identify candidate biobehavioral dimensions that confer risk for psychopathology.ObjectivesWe test whether lower efficiency of evidence accumulation (EEA), a computationally characterized individual difference variable that drives performance on the go/no-go and other neurocognitive tasks, is a risk factor for substance use in emerging adults.Methods and resultsIn an fMRI substudy within a sociobehavioral longitudinal study (n = 106), we find that lower EEA and reductions in a robust neural-level correlate of EEA (error-related activations in salience network structures) measured at ages 18–21 are both prospectively related to greater substance use during ages 22–26, even after adjusting for other well-known risk factors. Results from Bayesian model comparisons corroborated inferences from conventional hypothesis testing and provided evidence that both EEA and its neuroimaging correlates contain unique predictive information about substance use involvement.ConclusionsThese findings highlight EEA as a computationally characterized neurocognitive risk factor for substance use during a critical developmental period, with clear links to both neuroimaging measures and well-established formal theories of brain function.
Bayesian model-averaged meta-analysis allows quantification of evidence for both treatment effect... more Bayesian model-averaged meta-analysis allows quantification of evidence for both treatment effectiveness µ and across-study heterogeneity τ. We use the Cochrane Database of Systematic Reviews to develop discipline-wide empirical prior distributions for µ and τ for meta-analyses of binary and time-to-event clinical trial outcomes. First, we use 50% of the database to estimate parameters of different required parametric families. Second, we use the remaining 50% of the database to select the best-performing parametric families and explore essential assumptions about the presence or absence of the treatment effectiveness and across-study heterogeneity in real data. We find that most meta-analyses of binary outcomes are more consistent with the absence of the meta-analytic effect or heterogeneity while meta-analyses of time-to-event outcomes are more consistent with the presence of the meta-analytic effect or heterogeneity. Finally, we use the complete database-with close to half a million trial outcomes-to propose specific empirical prior distributions, both for the field in general and for specific medical subdisciplines. An example from acute respiratory infections demonstrates how the proposed prior distributions can be used to conduct a Bayesian model-averaged meta-analysis in the open-source software R and JASP.
Pearson's correlation is one of the most common measures of linear dependence. Recently, Bernardo... more Pearson's correlation is one of the most common measures of linear dependence. Recently, Bernardo (2015) introduced a flexible class of priors to study this measure in a Bayesian setting. For this large class of priors we show that the (marginal) posterior for Pearson's correlation coefficient and all of the posterior moments are analytic. Our results are available in the open-source software package JASP.
A putative relationship between markers for the serotonin system and the personality scale self-t... more A putative relationship between markers for the serotonin system and the personality scale self-transcendence (ST) and its subscale spiritual acceptance (SA) has been demonstrated in a previous PET study of 5-HT 1A receptor binding in healthy control subjects. The results could however not be replicated in a subsequent PET study at an independent centre. In this study, we performed a replication of our original study in a larger sample using Bayesian hypothesis testing to evaluate relative evidence both for and against this hypothesis. Methods: Regional 5-HT 1A receptor binding potential (BP ND) was examined in 50 healthy male subjects using PET with the radioligand [ 11 C]WAY100635. 5-HT 1A availability was calculated using the simplified reference tissue model (SRTM) yielding regional BP ND. ST and SA were measured using the Temperament and Character Inventory (TCI) questionnaire. Correlations between ST/SA scores and 5-HT 1A BP ND in frontal cortex, hippocampus and raphe nuclei were examined by calculation of default correlation Bayes factors (BFs) and replication BFs. Results: There were no significant correlations between 5-HT 1A receptor binding and ST/SA scores. Rather, five of six replication BFs provided moderate to strong evidence for no association between 5-HT 1A availability and ST/SA, while the remaining BF provided only weak evidence. Conclusion: We could not replicate our previous findings of an association between 5-HT 1A availability and the personality trait ST/SA. Rather, the Bayesian analysis provided evidence for a lack of correlation. Further research should focus on whether other components of the serotonin system may be related to ST or SA. This study also illustrates how Bayesian hypothesis testing allows for greater flexibility and more informative conclusions than traditional p-values, suggesting that this approach may be advantageous for analysis of molecular imaging data.
This article outlines a novel Bayesian approach to the testing and estimation of Pearson partial ... more This article outlines a novel Bayesian approach to the testing and estimation of Pearson partial correlations. By generalizing a Bayesian inference procedure for Pearson's correlation coefficient we obtain analytic expressions for the Bayes factor and for the (marginal) posterior distribution of a partial correlation coefficient. Full Bayesian inference can be achieved using only the sample size, the number of controlling variables and the relevant summary statistics, that is, the sample partial correlation. The present approach is illustrated with two empirical examples.
Linear regression analyses commonly involve two consecutive stages of statistical inquiry. In the... more Linear regression analyses commonly involve two consecutive stages of statistical inquiry. In the first stage, a single 'best' model is defined by a specific selection of relevant predictors; in the second stage, the regression coefficients of the winning model are used for prediction and for inference concerning the importance of the predictors. However, such second-stage inference ignores the model uncertainty from the first stage, resulting in overconfident parameter estimates that generalize poorly. These drawbacks can be overcome by model averaging, a technique that retains all models for inference, weighting each model's contribution by its posterior probability. Although conceptually straightforward, model averaging is rarely used in applied research, possibly due to the lack of easily accessible software. To bridge the gap between theory and practice, we provide a tutorial on linear regression using Bayesian model averaging in JASP, based on the BAS package in R. Firstly, we provide theoretical background on linear regression, Bayesian inference, and Bayesian model averaging. Secondly, we demonstrate the method on an example data set from the World Happiness Report. Lastly, we discuss limitations of model averaging and directions for dealing with violations of model assumptions. Keywords Bayesian inference • Bayesian model averaging • Linear regression Linear regression is a standard statistical procedure in which one continuous variable (known as the dependent, outcome, or criterion variable) is being accounted for by a set of continuous predictor variables (also known as independent variables, covariates, or predictors). For concreteness, consider a researcher who is interested in predicting people's happiness using a number of country-specific demographic indicators such as Gross Domestic Product (GDP), public safety, life expectancy, and many others. When all available predictors are included in the regression
A putative relationship between markers for the serotonin system and the personality scale self-t... more A putative relationship between markers for the serotonin system and the personality scale self-transcendence (ST) and its subscale spiritual acceptance (SA) has been demonstrated in a previous PET study of 5-HT 1A receptor binding in healthy control subjects. The results could however not be replicated in a subsequent PET study at an independent centre. In this study, we performed a replication of our original study in a larger sample using Bayesian hypothesis testing to evaluate relative evidence both for and against this hypothesis. Methods: Regional 5-HT 1A receptor binding potential (BP ND) was examined in 50 healthy male subjects using PET with the radioligand [ 11 C]WAY100635. 5-HT 1A availability was calculated using the simplified reference tissue model (SRTM) yielding regional BP ND. ST and SA were measured using the Temperament and Character Inventory (TCI) questionnaire. Correlations between ST/SA scores and 5-HT 1A BP ND in frontal cortex, hippocampus and raphe nuclei were examined by calculation of default correlation Bayes factors (BFs) and replication BFs. Results: There were no significant correlations between 5-HT 1A receptor binding and ST/SA scores. Rather, five of six replication BFs provided moderate to strong evidence for no association between 5-HT 1A availability and ST/SA, while the remaining BF provided only weak evidence. Conclusion: We could not replicate our previous findings of an association between 5-HT 1A availability and the personality trait ST/SA. Rather, the Bayesian analysis provided evidence for a lack of correlation. Further research should focus on whether other components of the serotonin system may be related to ST or SA. This study also illustrates how Bayesian hypothesis testing allows for greater flexibility and more informative conclusions than traditional p-values, suggesting that this approach may be advantageous for analysis of molecular imaging data.
In many statistical applications that concern mathematical psychologists, the concept of Fisher i... more In many statistical applications that concern mathematical psychologists, the concept of Fisher information plays an important role. In this tutorial we clarify the concept of Fisher information as it manifests itself across three different statistical paradigms. First, in the frequentist paradigm, Fisher information is used to construct hypothesis tests and confidence intervals using maximum likelihood estimators; second, in the Bayesian paradigm, Fisher information is used to define a default prior; lastly, in the minimum description length paradigm, Fisher information is used to measure model complexity.
We describe a general method that allows experimenters to quantify the evidence from the data of ... more We describe a general method that allows experimenters to quantify the evidence from the data of a direct replication attempt given data already acquired from an original study. These so-called replication Bayes factors are a reconceptualization of the ones introduced by Verhagen and Wagenmakers (Journal of Experimental Psychology: General, 143(4), 1457-1475 2014) for the common t test. This reconceptualization is computationally simpler and generalizes easily to most common experimental designs for which Bayes factors are available. Keywords Evidence synthesis • Hypothesis testing • Meta-analysis • Replication The past 5 years have witnessed a dramatic increase in interest for replication studies, largely in response to psychology's "crisis of confidence" (e.g., Pashler & Wagenmakers, 2012). While this crisis is not unique to the field of psychology by any means, psychologists have been at the forefront of efforts to assess and improve reproducibility in science by way of large-scale replication initiatives, such as the Reproducibility Project: Psychology (Open Science Collaboration, 2015), the Social Psychology special issue on replication (Nosek & Lakens, 2014), and the various ManyLabs efforts (Ebersole et al., 2016; Klein et al., 2014). Although the importance of direct replication has been contested by some (for an overview of the most common arguments see Zwaan, Etz, Lucas, & Donnellan, 2017), the increasing prominence of replication studies has prompted researchers to examine the question of how to assess, statistically, the degree to which a replication study succeeds or fails.
The New England journal of statistics in data science, 2024
We introduce the anytime-valid (AV) logrank test, a version of the logrank test that provides typ... more We introduce the anytime-valid (AV) logrank test, a version of the logrank test that provides type-I error guarantees under optional stopping and optional continuation. The test is sequential without the need to specify a maximum sample size or stopping rule, and allows for cumulative meta-analysis with type-I error control. The method can be extended to define anytime-valid confidence intervals. The logrank test is an instance of the martingale tests based on E-variables that have been recently developed. We demonstrate type-I error guarantees for the test in a semiparametric setting of proportional hazards, show explicitly how to extend it to ties and confidence sequences and indicate further extensions to the full Cox regression model. Using a Gaussian approximation on the logrank statistic, we show that the AV logrank test (which itself is always exact) has a similar rejection region to O'Brien-Fleming α-spending but with the potential to achieve 100% power by optional continuation. Although our approach to study design requires a larger sample size, the expected sample size is competitive by optional stopping.
Bayesian inference for rank-order problems is frustrated by the absence of an explicit likelihood... more Bayesian inference for rank-order problems is frustrated by the absence of an explicit likelihood function. This hurdle can be overcome by assuming a latent normal representation that is consistent with the ordinal information in the data: the observed ranks are conceptualized as an impoverished reflection of an underlying continuous scale, and inference concerns the parameters that govern the latent representation. We apply this generic data-augmentation method to obtain Bayes factors for three popular rank-based tests: the rank sum test, the signed rank test, and Spearman's ρ s .
Archive for History of Exact Sciences, May 30, 2023
This Editorial reports an exchange in form of a comment and reply on the article "History and Nat... more This Editorial reports an exchange in form of a comment and reply on the article "History and Nature of the Jeffreys-Lindley Paradox" (Arch Hist Exact Sci 77:25, 2023) by Eric-Jan Wagenmakers and Alexander Ly. 1 Comments by J. Gray, Editor-in-Chief AHES does not normally publish correspondence about an article, and would prefer to see scholarly disagreements dealt with in the form of subsequent articles. We are making an exception in this case because of the significant difficulties involved in the interpretation and mathematical formulation of the Jeffreys-Lindley paradox, and the way they affect historical interpretations. 2 Comment on "History and nature of the Jeffreys-Lindley paradox" by J. L. Cherry (Joshua L. Cherry is a US government employee his comment cannot be copyrighted) The Jeffreys-Lindley paradox involves disagreements between classical and Bayesian null hypothesis tests applied to the same observations. The two approaches can lead to opposite conclusions: the classicalp-value may be low enough that the null hypothesis would be rejected while the Bayesian posterior probability favors the null. The paradox, according to Lindley (1957), is that whatever the prior probability of B Jeremy Gray
Hypotheses concerning the distribution of multinomial proportions typically entail exact equality... more Hypotheses concerning the distribution of multinomial proportions typically entail exact equality constraints that can be evaluated using standard tests. Whenever researchers formulate inequality constrained hypotheses, however, they must rely on sampling-based methods that are relatively inefficient and computationally expensive. To address this problem we developed a bridge sampling routine that allows an efficient evaluation of multinomial inequality constraints. An empirical application showcases that bridge sampling outperforms current Bayesian methods, especially when relatively little posterior mass falls in the restricted parameter space. The method is extended to mixtures between equality and inequality constrained hypotheses.
RationaleSubstance use peaks during the developmental period known as emerging adulthood (ages 18... more RationaleSubstance use peaks during the developmental period known as emerging adulthood (ages 18–25), but not every individual who uses substances during this period engages in frequent or problematic use. Although individual differences in neurocognition appear to predict use severity, mechanistic neurocognitive risk factors with clear links to both behavior and neural circuitry have yet to be identified. Here, we aim to do so with an approach rooted in computational psychiatry, an emerging field in which formal models are used to identify candidate biobehavioral dimensions that confer risk for psychopathology.ObjectivesWe test whether lower efficiency of evidence accumulation (EEA), a computationally characterized individual difference variable that drives performance on the go/no-go and other neurocognitive tasks, is a risk factor for substance use in emerging adults.Methods and resultsIn an fMRI substudy within a sociobehavioral longitudinal study (n = 106), we find that lower EEA and reductions in a robust neural-level correlate of EEA (error-related activations in salience network structures) measured at ages 18–21 are both prospectively related to greater substance use during ages 22–26, even after adjusting for other well-known risk factors. Results from Bayesian model comparisons corroborated inferences from conventional hypothesis testing and provided evidence that both EEA and its neuroimaging correlates contain unique predictive information about substance use involvement.ConclusionsThese findings highlight EEA as a computationally characterized neurocognitive risk factor for substance use during a critical developmental period, with clear links to both neuroimaging measures and well-established formal theories of brain function.
Bayesian model-averaged meta-analysis allows quantification of evidence for both treatment effect... more Bayesian model-averaged meta-analysis allows quantification of evidence for both treatment effectiveness µ and across-study heterogeneity τ. We use the Cochrane Database of Systematic Reviews to develop discipline-wide empirical prior distributions for µ and τ for meta-analyses of binary and time-to-event clinical trial outcomes. First, we use 50% of the database to estimate parameters of different required parametric families. Second, we use the remaining 50% of the database to select the best-performing parametric families and explore essential assumptions about the presence or absence of the treatment effectiveness and across-study heterogeneity in real data. We find that most meta-analyses of binary outcomes are more consistent with the absence of the meta-analytic effect or heterogeneity while meta-analyses of time-to-event outcomes are more consistent with the presence of the meta-analytic effect or heterogeneity. Finally, we use the complete database-with close to half a million trial outcomes-to propose specific empirical prior distributions, both for the field in general and for specific medical subdisciplines. An example from acute respiratory infections demonstrates how the proposed prior distributions can be used to conduct a Bayesian model-averaged meta-analysis in the open-source software R and JASP.
Pearson's correlation is one of the most common measures of linear dependence. Recently, Bernardo... more Pearson's correlation is one of the most common measures of linear dependence. Recently, Bernardo (2015) introduced a flexible class of priors to study this measure in a Bayesian setting. For this large class of priors we show that the (marginal) posterior for Pearson's correlation coefficient and all of the posterior moments are analytic. Our results are available in the open-source software package JASP.
A putative relationship between markers for the serotonin system and the personality scale self-t... more A putative relationship between markers for the serotonin system and the personality scale self-transcendence (ST) and its subscale spiritual acceptance (SA) has been demonstrated in a previous PET study of 5-HT 1A receptor binding in healthy control subjects. The results could however not be replicated in a subsequent PET study at an independent centre. In this study, we performed a replication of our original study in a larger sample using Bayesian hypothesis testing to evaluate relative evidence both for and against this hypothesis. Methods: Regional 5-HT 1A receptor binding potential (BP ND) was examined in 50 healthy male subjects using PET with the radioligand [ 11 C]WAY100635. 5-HT 1A availability was calculated using the simplified reference tissue model (SRTM) yielding regional BP ND. ST and SA were measured using the Temperament and Character Inventory (TCI) questionnaire. Correlations between ST/SA scores and 5-HT 1A BP ND in frontal cortex, hippocampus and raphe nuclei were examined by calculation of default correlation Bayes factors (BFs) and replication BFs. Results: There were no significant correlations between 5-HT 1A receptor binding and ST/SA scores. Rather, five of six replication BFs provided moderate to strong evidence for no association between 5-HT 1A availability and ST/SA, while the remaining BF provided only weak evidence. Conclusion: We could not replicate our previous findings of an association between 5-HT 1A availability and the personality trait ST/SA. Rather, the Bayesian analysis provided evidence for a lack of correlation. Further research should focus on whether other components of the serotonin system may be related to ST or SA. This study also illustrates how Bayesian hypothesis testing allows for greater flexibility and more informative conclusions than traditional p-values, suggesting that this approach may be advantageous for analysis of molecular imaging data.
This article outlines a novel Bayesian approach to the testing and estimation of Pearson partial ... more This article outlines a novel Bayesian approach to the testing and estimation of Pearson partial correlations. By generalizing a Bayesian inference procedure for Pearson's correlation coefficient we obtain analytic expressions for the Bayes factor and for the (marginal) posterior distribution of a partial correlation coefficient. Full Bayesian inference can be achieved using only the sample size, the number of controlling variables and the relevant summary statistics, that is, the sample partial correlation. The present approach is illustrated with two empirical examples.
Linear regression analyses commonly involve two consecutive stages of statistical inquiry. In the... more Linear regression analyses commonly involve two consecutive stages of statistical inquiry. In the first stage, a single 'best' model is defined by a specific selection of relevant predictors; in the second stage, the regression coefficients of the winning model are used for prediction and for inference concerning the importance of the predictors. However, such second-stage inference ignores the model uncertainty from the first stage, resulting in overconfident parameter estimates that generalize poorly. These drawbacks can be overcome by model averaging, a technique that retains all models for inference, weighting each model's contribution by its posterior probability. Although conceptually straightforward, model averaging is rarely used in applied research, possibly due to the lack of easily accessible software. To bridge the gap between theory and practice, we provide a tutorial on linear regression using Bayesian model averaging in JASP, based on the BAS package in R. Firstly, we provide theoretical background on linear regression, Bayesian inference, and Bayesian model averaging. Secondly, we demonstrate the method on an example data set from the World Happiness Report. Lastly, we discuss limitations of model averaging and directions for dealing with violations of model assumptions. Keywords Bayesian inference • Bayesian model averaging • Linear regression Linear regression is a standard statistical procedure in which one continuous variable (known as the dependent, outcome, or criterion variable) is being accounted for by a set of continuous predictor variables (also known as independent variables, covariates, or predictors). For concreteness, consider a researcher who is interested in predicting people's happiness using a number of country-specific demographic indicators such as Gross Domestic Product (GDP), public safety, life expectancy, and many others. When all available predictors are included in the regression
A putative relationship between markers for the serotonin system and the personality scale self-t... more A putative relationship between markers for the serotonin system and the personality scale self-transcendence (ST) and its subscale spiritual acceptance (SA) has been demonstrated in a previous PET study of 5-HT 1A receptor binding in healthy control subjects. The results could however not be replicated in a subsequent PET study at an independent centre. In this study, we performed a replication of our original study in a larger sample using Bayesian hypothesis testing to evaluate relative evidence both for and against this hypothesis. Methods: Regional 5-HT 1A receptor binding potential (BP ND) was examined in 50 healthy male subjects using PET with the radioligand [ 11 C]WAY100635. 5-HT 1A availability was calculated using the simplified reference tissue model (SRTM) yielding regional BP ND. ST and SA were measured using the Temperament and Character Inventory (TCI) questionnaire. Correlations between ST/SA scores and 5-HT 1A BP ND in frontal cortex, hippocampus and raphe nuclei were examined by calculation of default correlation Bayes factors (BFs) and replication BFs. Results: There were no significant correlations between 5-HT 1A receptor binding and ST/SA scores. Rather, five of six replication BFs provided moderate to strong evidence for no association between 5-HT 1A availability and ST/SA, while the remaining BF provided only weak evidence. Conclusion: We could not replicate our previous findings of an association between 5-HT 1A availability and the personality trait ST/SA. Rather, the Bayesian analysis provided evidence for a lack of correlation. Further research should focus on whether other components of the serotonin system may be related to ST or SA. This study also illustrates how Bayesian hypothesis testing allows for greater flexibility and more informative conclusions than traditional p-values, suggesting that this approach may be advantageous for analysis of molecular imaging data.
Uploads
Papers by Alexander Ly