Papers by František Bartoš
BMC public health, Jun 26, 2024
Background Although physical activity (PA) is associated with significant health benefits, only a... more Background Although physical activity (PA) is associated with significant health benefits, only a small percentage of adolescents meet recommended PA levels. This systematic review with meta-analysis explored the modifiable determinants of adolescents' device-based PA and/or sedentary behaviour (SB), evaluated in previous interventions and examined the associations between PA/SB and these determinants in settings. Methods A search was conducted on five electronic databases, including papers published from January 2010 to July 2023. Randomized Controlled Trials (RCTs) or Controlled Trials (CTs) measuring adolescents' device-based PA/ SB and their modifiable determinants at least at two time points: pre-and post-intervention were considered eligible. PA/SB and determinants were the main outcomes. Modifiable determinants were classified after data extraction adopting the social-ecological perspective. Robust Bayesian meta-analyses (RoBMA) were performed per each study setting. Outcomes identified in only one study were presented narratively. The risk of bias for each study and the certainty of the evidence for each meta-analysis were evaluated. The publication bias was also checked. PROSPERO ID: CRD42021282874. Results Fourteen RCTs (eight in school, three in school and family, and one in the family setting) and one CT (in the school setting) were included. Fifty-four modifiable determinants were identified and were combined into 33 broader determinants (21 individual-psychological, four individual-behavioural, seven interpersonal, and one institutional). RoBMAs revealed none or negligible pooled intervention effects on PA/SB or determinants in all settings. The certainty of the evidence of the impact of interventions on outcomes ranged from very low to low. Narratively,
Meta-regression constitutes an essential meta-analytic tool for investigating sources of heteroge... more Meta-regression constitutes an essential meta-analytic tool for investigating sources of heterogeneity and assessing the impact of moderators. However, existing methods for meta-regression have limitations that include inadequate consideration of model uncertainty and poor performance under publication bias. To overcome these limitations, we extend robust Bayesian meta-analysis (RoBMA) to meta-regression (RoBMA-regression). RoBMA-regression allows for moderator analyses while simultaneously taking into account the uncertainties about the presence and impact of other factors (i.e., the main effect, heterogeneity, publication bias, and other potential moderators). We offer guidance on how to specify prior distributions for continuous and categorical moderators and introduce a Savage-Dickey density ratio test to quantify the evidence for and against the presence of the effect at different levels of categorical moderators. We illustrate RoBMA-regression in an empirical example and demon...
Behavior Research Methods, Jun 5, 2023
The multibridge R package allows a Bayesian evaluation of informed hypotheses H r applied to freq... more The multibridge R package allows a Bayesian evaluation of informed hypotheses H r applied to frequency data from an independent binomial or multinomial distribution. multibridge uses bridge sampling to efficiently compute Bayes factors for the following hypotheses concerning the latent category proportions θ: (a) hypotheses that postulate equality constraints (e.g., θ 1 = θ 2 = θ 3); (b) hypotheses that postulate inequality constraints (e.g., θ 1 < θ 2 < θ 3 or θ 1 > θ 2 > θ 3); (c) hypotheses that postulate combinations of inequality constraints and equality constraints (e.g., θ 1 < θ 2 = θ 3); and (d) hypotheses that postulate combinations of (a)-(c) (e.g., θ 1 < (θ 2 = θ 3), θ 4). Any informed hypothesis H r may be compared against the encompassing hypothesis H e that all category proportions vary freely, or against the null hypothesis H 0 that all category proportions are equal. multibridge facilitates the fast and accurate comparison of large models with many constraints and models for which relatively little posterior mass falls in the restricted parameter space. This paper describes the underlying methodology and illustrates the use of multibridge through fully reproducible examples.
Stat, Jul 18, 2023
A staple of Bayesian model comparison and hypothesis testing Bayes factors are often used to quan... more A staple of Bayesian model comparison and hypothesis testing Bayes factors are often used to quantify the relative predictive performance of two rival hypotheses. The computation of Bayes factors can be challenging, however, and this has contributed to the popularity of convenient approximations such as the Bayesian information criterion (BIC). Unfortunately, these approximations can fail in the case of informed prior distributions. Here, we address this problem by outlining an approximation to informed Bayes factors for a focal parameter . The approximation is computationally simple and requires only the maximum likelihood estimate and its standard error. The approximation uses an estimated likelihood of and assumes that the posterior distribution for is unaffected by the choice of prior distribution for the nuisance parameters. The resulting Bayes factor for the null hypothesis versus the alternative hypothesis is then easily obtained using the Savage–Dickey density ratio. Three real‐data examples highlight the speed and closeness of the approximation compared with bridge sampling and Laplace's method. The proposed approximation facilitates Bayesian reanalyses of standard frequentist results, encourages application of Bayesian tests with informed priors, and alleviates the computational challenges that often frustrate both Bayesian sensitivity analyses and Bayes factor design analyses. The approximation is shown to suffer under small sample sizes and when the posterior distribution of the focal parameter is substantially influenced by the prior distributions on the nuisance parameters. The proposed methodology may also be used to approximate the posterior distribution for under .
Meta-psychology, Nov 8, 2022
The replication crisis in psychology has led to an increased concern regarding the false discover... more The replication crisis in psychology has led to an increased concern regarding the false discovery rate (FDR)the proportion of false positive findings among all significant findings. In this article, we compare two previously proposed solutions for decreasing the FDR: increasing statistical power and decreasing significance level α. First, we provide an intuitive explanation for α, power, and FDR to improve the understanding of these concepts. Second, we investigate the relationship between α and power. We show that for decreasing FDR, reducing α is more efficient than increasing power. We suggest that researchers interested in reducing the FDR should decrease α rather than increase power. By investigating the relative importance of both α level and power, we connect the literature on these topics and our results have implications for increasing the reproducibility of psychological science.
Systematic Reviews, Jun 19, 2020
Background: Pre-and post-partum depression is a common mood disorder with detrimental effects on ... more Background: Pre-and post-partum depression is a common mood disorder with detrimental effects on both mother and child. The aim of the proposed review is to summarize evidence related to the effects of both pre-and post-partum depression on child behavior and development from birth to preschool age. In particular, our review will address mutual relations between pre-and post-partum depression in order to determine whether pre-and post-partum depression predict child psychological outcomes independently, whether there is an effect of timing of depression on child outcomes, whether pre-and post-partum depression interact to affect child outcomes, and whether the effect of pre-partum depression is mediated by depression after child's birth. Methods: We will include prospective longitudinal studies that report data about the effects of both pre-and postpartum depression on child psychological outcomes as published in peer-reviewed academic journals since January 1998. We will search EMBASE, MEDLINE, PsycARTICLES, PsycINFO, ISI Web of Science, Scopus, and Wiley Online databases to identify original research articles written in English. Two independent reviewers will screen search results in two stages: (i) titles and abstracts and (ii) full text. The first one will extract data into tables, while the latter will verify whether the data extracted are correct. We will assess the risk of bias in the selected studies using the Critical Appraisal Skills Programme (CASP), Cohort Study Checklist. The results of the review will be reported in a narrative form. If there are sufficient data available, a meta-analysis will be conducted using metaSEM package in R. Discussion: The proposed review will be the first systematic review summarizing the effects of both pre-and postpartum depression on child psychological development and behavior from birth to preschool age. The results of such a review may contribute to a better understanding of mutual relations between pre-and post-partum depression in their effects on child outcomes. They may also shed light on what periods in early human development are most vulnerable to the effects of maternal depression.
Advances in methods and practices in psychological science, Jul 1, 2022
Meta-analyses are essential for cumulative science, but their validity can be compromised by publ... more Meta-analyses are essential for cumulative science, but their validity can be compromised by publication bias. To mitigate the impact of publication bias, one may apply publication-bias-adjustment techniques such as precision-effect test and precision-effect estimate with standard errors (PET-PEESE) and selection models. These methods, implemented in JASP and R, allow researchers without programming experience to conduct state-of-the-art publication-bias-adjusted meta-analysis. In this tutorial, we demonstrate how to conduct a publication-bias-adjusted meta-analysis in JASP and R and interpret the results. First, we explain two frequentist bias-correction methods: PET-PEESE and selection models. Second, we introduce robust Bayesian meta-analysis, a Bayesian approach that simultaneously considers both PET-PEESE and selection models. We illustrate the methodology on an example data set, provide an instructional video ( https://bit.ly/pubbias ) and an R-markdown script ( https://osf.io/uhaew/ ), and discuss the interpretation of the results. Finally, we include concrete guidance on reporting the meta-analytic results in an academic article.
Breastfeeding Medicine, Aug 31, 2021
Background and Objective: Synthetic oxytocin (synOT) is a widely used drug to induce or accelerat... more Background and Objective: Synthetic oxytocin (synOT) is a widely used drug to induce or accelerate labor and to prevent postpartum hemorrhage. Although some studies indicate there are associations between intrapartum synOT and impaired breastfeeding initiation or earlier cessation, the long-term effects of synOT on breastfeeding are largely understudied. The aim of this study was to examine the effects of synOT on breastfeeding status during the first 9 months postpartum. Materials and Methods: The women were recruited from five maternity hospitals during prenatal medical checkups or postpartum hospital stay. They reported their breastfeeding status on discharge from maternity hospital (mean 4.54 days postpartum) (N = 439), at 6 weeks (N = 439), and at 9 months postpartum (N = 274). The data related to synOT administration were extracted from the medical records. Results: In the analysis adjusted for maternal age, parity, educational level, marital status, child's sex, delivery mode, and labor analgesia/anesthesia, intrapartum administration of synOT predicted a lower probability of exclusive breastfeeding on discharge from maternity hospital (odds ratio = 0.37; p = 0.006), but we observed no effect on breastfeeding status at 6 weeks or 9 months postpartum. Conclusion: Our results suggest that adverse effects of synOT on breastfeeding do not persist beyond the first postpartum days.
Cash transfers are among the most popular poverty interventions. Indeed the charity evaluator Giv... more Cash transfers are among the most popular poverty interventions. Indeed the charity evaluator GiveWell even lists GiveDirectly-a charity that directly sends your donations as cash to people in extreme poverty-as one of their top-rated charities [https://www.givewell.org/charities/give-directly]. McGuire, Kaiser, and Bach-Mortensen 1 conducted a timely and comprehensive meta-analysis on the impact of cash transfers on subjective well-being and mental health, featuring 45 studies with a combined total of 116,999 individuals. McGuire and colleagues 1 conclude "CTs [cash transfers] have a small but statistically significant positive effect on both SWB [subjective well-being] (Cohen's d = 0.13, 95% confidence interval (CI) 0.09, 0.18) and MH [mental health] (d = 0.07, 95% CI 0.05, 0.09) among recipients." We show that once publication bias is properly accounted for, this effect isdepending on the outcome measure-either greatly reduced or completely diminished. McGuire and colleagues 1 test for publication bias using Egger regression and p-curve. Neither the Egger regression nor the p-curve shows evidence for publication bias, and they conclude, "In general, there appears little evidence of publication bias or cherry-picking of results." However, both Egger regression and p-curve were shown to perform poorly under high heterogeneity 2,3,4,5,6,7 .
Proceedings of the National Academy of Sciences of the United States of America, Jul 19, 2022
arXiv (Cornell University), Jun 24, 2023
The delayed and incomplete availability of historical findings and the lack of integrative and us... more The delayed and incomplete availability of historical findings and the lack of integrative and userfriendly software hampers the reliable interpretation of new clinical data. We developed a free, open, and user-friendly clinical trial aggregation program combining a large and representative sample of existing trial data with the latest classical and Bayesian meta-analytical models, including clear output visualizations. Our software is of particular interest for (post-graduate) educational programs (e.g., medicine, epidemiology) and global health initiatives. We demonstrate the database, interface, and plot functionality with a recent randomized controlled trial on effective epileptic seizure reduction in children treated for a parasitic brain infection. The single trial data is placed into context and we show how to interpret new results against existing knowledge instantaneously. Our program is of particular interest to those working on the contextualizing of medical findings. It may facilitate the advancement of global clinical progress as efficiently and openly as possible and simulate further bridging clinical data with the latest biostatistical models.
arXiv (Cornell University), Jun 20, 2023
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.
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Papers by František Bartoš