scholarly journals Correlation Detection with and without the Theories of Conditionals: A model update of Hattori & Oaksford (2007)

2018 ◽  
Author(s):  
Tatsuji Takahashi ◽  
Kuratomo Oyo ◽  
Akihiro Tamatsukuri ◽  
Kohki Higuchi
Keyword(s):  
Computational Analysis ◽  
Meta Analysis ◽  
Small Samples ◽  
Stage Theory ◽  
Square Root ◽  
Statistical Independence ◽  
Rational Analysis ◽  
Independence Test ◽  
Causal Induction ◽  
Model Update

AbstractWe view observational causal induction as a statistical independence test under rarity assumption. This paper complements the two-stage theory of causal induction proposed by Hattori and Oaksford (2007) with a computational analysis. We show that their dual-factor heuristic (DFH) model has a rational account as the square root of the index of (non-)independence under extreme rarity assumption, contrary to the criticism that the DFH model is non-normative (e.g., Lu et al., 2008). We introduce a model that considers the proportion of assumed-to-be rare instances (pARIs), which is the probability of biconditionals (according to several theories of compound conditionals) and can be seen as a simplified version of the DFH model. While being a single conditional probability, pARIs approximates the non-independence measure, the square of DFH. In reproducing the meta-analysis in Hattori and Oaksford (2007), we confirm that pARIs and DFH have the same level of descriptive adequacy, and that the two models have the highest fit among more than 40 models. Then, we critically examine the computer simulations which were central to the rational analysis in Hattori and Oaksford (2007). We point out two problems in their simluations: samples in some of the simulations being restricted to generative ones, and in-definite values of models because of the small samples. In the light of especially the latter problem of definability, pARIs shows higher applicability.

scholarly journals Random Permutations, Non-Decreasing Subsequences and Statistical Independence

Symmetry ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 1415
Author(s):  
Jesús E. García ◽  
Verónica A. González-López
Keyword(s):  
Random Variables ◽  
Continuous Data ◽  
Random Permutations ◽  
Statistical Independence ◽  
Independence Test ◽  
Independence Tests ◽  
Present Procedure ◽  
Longest Increasing Subsequence

In this paper, we show how the longest non-decreasing subsequence, identified in the graph of the paired marginal ranks of the observations, allows the construction of a statistic for the development of an independence test in bivariate vectors. The test works in the case of discrete and continuous data. Since the present procedure does not require the continuity of the variables, it expands the proposal introduced in Independence tests for continuous random variables based on the longest increasing subsequence (2014). We show the efficiency of the procedure in detecting dependence in real cases and through simulations.

scholarly journals An Independence Test Based on Symbolic Time Series

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Wiston Adrián Risso
Keyword(s):  
Time Series ◽  
Monte Carlo ◽  
Time Series Analysis ◽  
Monte Carlo Simulations ◽  
Degrees Of Freedom ◽  
Chaotic Systems ◽  
Small Samples ◽  
Independence Test ◽  
Series Analysis ◽  
Symbolic Time Series Analysis

An independence test based on symbolic time series analysis (STSA) is developed. Considering an independent symbolic time series there is a statistic asymptotically distributed as a CHI-2 with n-1 degrees of freedom. Size and power experiments for small samples were conducted applying Monte Carlo simulations and comparing the results with BDS and runs test. The introduced test shows a good performance detecting independence in nonlinear and chaotic systems.

scholarly journals Placebo response in trials of drug treatments for cancer-related fatigue: a systematic review, meta-analysis and meta-regression

2020 ◽  
Vol 10 (4) ◽  
pp. 385-394 ◽  
Author(s):  
Rocio Roji ◽  
Patrick Stone ◽  
Federico Ricciardi ◽  
Bridget Candy
Keyword(s):  
Systematic Review ◽  
Meta Analysis ◽  
Placebo Response ◽  
Risk Of Bias ◽  
Small Samples ◽  
Contributing Factors ◽  
Cancer Related Fatigue ◽  
Study Results ◽  
Meta Regression ◽  
Multiple Drugs

BackgroundCancer-related fatigue (CRF) is one of the most distressing symptoms experienced by patients. There is no gold standard treatment, although multiple drugs have been tested with little evidence of efficacy. Randomised controlled trials (RCTs) of these drugs have commented on the existence or size of the placebo response (PR). The objective of this systematic review was to establish the magnitude of the PR in RCTs of drugs to relieve CRF and to identify contributing factors.MethodRCTs were included in which the objective was to treat CRF. A meta-analysis was conducted using the standardised mean change (SMC) between baseline and final measurement in the placebo group. To explore factors that may be associated with the PR (eg, population or drug), a meta-regression was undertaken. Risk of bias was assessed using the revised Cochrane tool.ResultsFrom 3916 citations, 30 relevant RCTs were identified. All had limitations that increased their risk of bias. The pooled SMC in reduction in fatigue status in placebo groups was −0.23 (95% confidence intervals −0.42 to −0.04). None of the variables analysed in the meta-regression were statistically significant related to PR.ConclusionThere is some evidence, based on trials with small samples, that the PR in trials testing drugs for CRF is non-trivial in size and statistically significant. We recommend that researchers planning drug studies in CRF should consider implementing alternative trial designs to better account for PR and decrease impact on the study results.

Questions for Meta-Analysis

1997 ◽  
Vol 81 (1) ◽  
pp. 3-15 ◽  
Author(s):  
David Sohn
Keyword(s):  
Scientific Discovery ◽  
Meta Analysis ◽  
Rational Analysis ◽  
Individual Study ◽  
Conceptual Foundation ◽  
Psychological Science ◽  
Present Essay ◽  
History Of ◽  
The Individual ◽  
Successful Science

In spite of an abundance of data, the empirical evidence as yet does not make clear whether meta-analysis will bring about progress in psychological science. Therefore, it is still useful and desirable to engage in rational analysis of the methodology. Such analysis is done in the present essay by posing five questions that go to the logical and conceptual foundation of meta-analysis. The questions are (a) What are the grounds for believing that the review of the literature, even a quantitative one, will bring about scientific discovery? (b) Why is the individual study devalued when the history of successful science seems largely the story of the success of the individual study? (c) What is the rationale for believing that data analysis by itself can markedly improve the fortunes of psychological science? (d) Is there a basis for claims made on behalf of meta-analysis that it is more accurate than either the traditional literature review or the individual study? (e) Is there justification for the claim that de facto meta-analysis has been used effectively in physical science?

scholarly journals Prevalence of Epstein–Barr virus antibodies in different age groups in Europe and Asia: a systematic review and meta-analysis

2021 ◽  
Vol 65 (3) ◽  
pp. 276-286
Author(s):  
Tatyana V. Solomay ◽  
Tatyana A. Semenenko ◽  
Alexey I. Blokh
Keyword(s):  
Systematic Review ◽  
Growth Rate ◽  
Epstein Barr Virus ◽  
Meta Analysis ◽  
Age Groups ◽  
Maximum Growth ◽  
Small Samples ◽  
Barr Virus ◽  
Cochrane Reviews ◽  
Epstein Barr

Introduction. Attempts to assess the prevalence of antibodies (seroprevalence) to the Epstein-Barr virus have been made several times. Still, a complete understanding of this issue has not been reached due to the small samples of the surveyed. The goal is to evaluate seroprevalence in different age groups in Europe and Asia using a systematic review and meta-analysis. Material and methods. The search for publications was carried out on PubMed, Cochrane Reviews/CochraneLibrary, eLibrary, Cyberleninka, Researchgate from May 6 to 30, 2020. A total of 2,364 articles were found, 12 of which were included in the study. Seroprevalence to Epstein-Barr virus was determined in 67,561 individuals aged 0 to 80 years. The research results were distributed by age groups, continents (Europe and Asia), and their implementation (2000-2012 and 2013-2019) and subjected to meta-analysis. Results. Minimal seroprevalence was detected among children under 1 and 1-2 years of age (53.3 and 50.9%). With increasing age, it grew, and people over 18 years of age were more than 90%. In 2013-2019, the index value (68.9%) was significantly higher than in 2000-2012 (89.6%). In Asian countries in 2000-2019, seroprevalence (86.7%) was considerably higher than in Europe (76.3%). The highest growth rate was observed in 7-14 years. In 2000-2012, the maximum growth rate of seroprevalence occurred in 15-17 years and 2013-2019 - 3-6 years. For all age groups, the growth rate was higher in Europe than in Asia and 2013-2019 compared to 2000-2012. Conclusion. The meta-analysis revealed differences in seroprevalence depending on age and territory of residence and the growth of indices in the trend.

scholarly journals Telomeres as integrative markers of exposure to stress and adversity: A systematic review and meta-analysis

2018 ◽  
Author(s):  
Gillian V. Pepper ◽  
Melissa Bateson ◽  
Daniel Nettle
Keyword(s):  
Physical Activity ◽  
Psychiatric Illness ◽  
Meta Analysis ◽  
Small Samples ◽  
Association Strength ◽  
Common Currency ◽  
Causal Interpretation ◽  
Cross Sectional ◽  
Weak Association ◽  
Physical Diseases

AbstractTelomeres have been proposed as a biomarker that integrates the impacts of different kinds of stress and adversity into a common currency. There has as yet been no overall comparison of how different classes of exposure associate with telomeres. We present a meta-analysis of the literature relating telomere measures to stresses and adversities in humans. The analysed dataset contained 543 associations from 138 studies involving 402,116 people. Overall, there was a weak association between telomere variables and exposures (greater adversity, shorter telomeres:r= −0.15, 95% CI - 0.18 to −0.11). This was not driven by any one type of exposure, since significant associations were found separately for physical diseases, environmental hazards, nutrition, psychiatric illness, smoking, physical activity, psychosocial and socioeconomic exposures. Methodological features of the studies did not explain any substantial proportion of the heterogeneity in association strength. There was, however, evidence consistent with publication bias, with unexpectedly strong negative associations reported by studies with small samples. Restricting analysis to sample sizes greater than 100 attenuated the overall association substantially (r= −0.09, 95% CI −0.13 to −0.05). Most studies were underpowered to detect the typical association magnitude. The literature is dominated by cross-sectional and correlational studies which makes causal interpretation problematic.

scholarly journals Temporal variation in lymphocyte proteomics

2021 ◽  
Author(s):  
Michaela A McCown ◽  
Carolyn Allen ◽  
Daniel D Machado ◽  
Hannah Boekweg ◽  
Yiran Liang ◽  
...  
Keyword(s):  
Meta Analysis ◽  
Small Sample ◽  
Lymphocytic Leukemia ◽  
Small Samples ◽  
Tumor Evolution ◽  
Multiple Time ◽  
Time Points ◽  
Asymptomatic Stage ◽  
Multiple Time Points ◽  
Over Time

Chronic Lymphocytic Leukemia (CLL) is a slow progressing disease, characterized by a long asymptomatic stage followed by a symptomatic stage during which patients receive treatment. While proteomic studies have discovered differential pathways in CLL, the proteomic evolution of CLL during the asymptomatic stage has not been studied. In this pilot study, we show that by using small sample sizes comprising ~145 cells, we can detect important features of CLL necessary for studying tumor evolution. Our small samples are collected at two time points and reveal large proteomic changes in healthy individuals over time. A meta-analysis of two CLL proteomic papers showed little commonality in differentially expressed proteins and demonstrates the need for larger control populations sampled over time. To account for proteomic variability between time points and individuals, large control populations sampled at multiple time points are necessary for understanding CLL progression. Data is available via ProteomeXchange with identifier PXD027429.

scholarly journals The Effectiveness of Web-Based Interventions Delivered to Children and Young People With Neurodevelopmental Disorders: Systematic Review and Meta-Analysis (Preprint)

2019 ◽  
Author(s):  
Kareem Khan ◽  
Charlotte L Hall ◽  
E Bethan Davies ◽  
Chris Hollis ◽  
Cris Glazebrook
Keyword(s):  
Young People ◽  
Neurodevelopmental Disorders ◽  
Psychological Symptoms ◽  
Meta Analysis ◽  
Neurodevelopmental Disorder ◽  
Autism Spectrum ◽  
Small Samples ◽  
Long Term Conditions ◽  
Web Based ◽  
Children And Young People

BACKGROUND The prevalence of certain neurodevelopmental disorders, specifically autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD), has been increasing over the last four decades. Nonpharmacological interventions are available that can improve outcomes and reduce associated symptoms such as anxiety, but these are often difficult to access. Children and young people are using the internet and digital technology at higher rates than any other demographic, but although Web-based interventions have the potential to improve health outcomes in those with long-term conditions, no previous reviews have investigated the effectiveness of Web-based interventions delivered to children and young people with neurodevelopmental disorders. OBJECTIVE This study aimed to review the effectiveness of randomized controlled trials (RCTs) of Web-based interventions delivered to children and young people with neurodevelopmental disorders. METHODS Six databases and one trial register were searched in August and September 2018. RCTs were included if they were published in a peer-reviewed journal. Interventions were included if they (1) aimed to improve the diagnostic symptomology of the targeted neurodevelopmental disorder or associated psychological symptoms as measured by a valid and reliable outcome measure; (2) were delivered on the Web; (3) targeted a youth population (aged ≤18 years or reported a mean age of ≤18 years) with a diagnosis or suspected diagnosis of a neurodevelopmental disorder. Methodological quality was rated using the Joanna Briggs Institute Critical Appraisal Checklist for RCTs. RESULTS Of 5140 studies retrieved, 10 fulfilled the inclusion criteria. Half of the interventions were delivered to children and young people with ASDs with the other five targeting ADHD, tic disorder, dyscalculia, and specific learning disorder. In total, 6 of the 10 trials found that a Web-based intervention was effective in improving condition-specific outcomes or reducing comorbid psychological symptoms in children and young people. The 4 trials that failed to find an effect were all delivered by apps. The meta-analysis was conducted on five of the trials and did not show a significant effect, with a high level of heterogeneity detected (n=182 [33.4%, 182/545], 5 RCTs; pooled standardized mean difference=–0.39; 95% CI –0.98 to 0.20; Z=–1.29; <italic>P</italic>=.19 [I<sup>2</sup>=72%; <italic>P</italic>=.006]). CONCLUSIONS Web-based interventions can be effective in reducing symptoms in children and young people with neurodevelopmental disorders; however, caution should be taken when interpreting these findings owing to methodological limitations, the minimal number of papers retrieved, and small samples of included studies. Overall, the number of studies was small and mainly limited to ASD, thus restricting the generalizability of the findings. CLINICALTRIAL PROSPERO International Prospective Register of Systematic Reviews: CRD42018108824; http://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42018108824

scholarly journals A framework for meta-analysis of prediction model studies with binary and time-to-event outcomes

2018 ◽  
Vol 28 (9) ◽  
pp. 2768-2786 ◽  
Author(s):  
Thomas PA Debray ◽  
Johanna AAG Damen ◽  
Richard D Riley ◽  
Kym Snell ◽  
Johannes B Reitsma ◽  
...  
Keyword(s):  
Prediction Model ◽  
Prediction Models ◽  
Meta Analysis ◽  
Predictive Performance ◽  
R Package ◽  
Small Samples ◽  
Time To Event ◽  
Model Studies ◽  
Framingham Risk ◽  
Study Heterogeneity

It is widely recommended that any developed—diagnostic or prognostic—prediction model is externally validated in terms of its predictive performance measured by calibration and discrimination. When multiple validations have been performed, a systematic review followed by a formal meta-analysis helps to summarize overall performance across multiple settings, and reveals under which circumstances the model performs suboptimal (alternative poorer) and may need adjustment. We discuss how to undertake meta-analysis of the performance of prediction models with either a binary or a time-to-event outcome. We address how to deal with incomplete availability of study-specific results (performance estimates and their precision), and how to produce summary estimates of the c-statistic, the observed:expected ratio and the calibration slope. Furthermore, we discuss the implementation of frequentist and Bayesian meta-analysis methods, and propose novel empirically-based prior distributions to improve estimation of between-study heterogeneity in small samples. Finally, we illustrate all methods using two examples: meta-analysis of the predictive performance of EuroSCORE II and of the Framingham Risk Score. All examples and meta-analysis models have been implemented in our newly developed R package “metamisc”.

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