scholarly journals ON SOME METHODOLOGICAL ASPECTS OF THE STUDY OF HUMAN INDIVIDUALITY

2019 ◽  
Vol 12 (2) ◽  
pp. 29-40
Author(s):  
A Yu Kalugin
Keyword(s):  
Confidence Intervals ◽  
Effect Size ◽  
Meta Analysis ◽  
Significance Level ◽  
Hidden Data ◽  
Restriction Of Range ◽  
Methodological Aspects ◽  
Nonlinear Correlations ◽  
Maximal Information Coefficient ◽  
Different Levels

Human individuality, presented on different levels (from biological to social ones), is of a high interest in Russian psychology, and the method of correlation design is widely used among researches, because it allows revealing relationships between multi-level properties of individuality. The present article examines several methodical aspects of the correlation analysis implementation, discussing problems and possible solutions. In particular, it considers the issue of nonlinear dependencies (parabolic, hyperbolic etc.), which are impossible to reveal by common correlation methods, but which can be uncovered by using nonlinear correlations, such as correlation index, correlation ratio, maximal information coefficient, distance correlation, maximal correlation, “partial moments” method. Furthermore, it considers the necessity of visualizing variables correlation (scatterplots) that enables to reveal hidden data structures, for example, subgroups. Special attention is paid to correlations corrections for restriction of range and related difficulties that are well-known, but scarcely researched in Russian psychology. In process of investigating plentiful pairwise correlations between individuality properties on different levels it is important to consider anissue of multiple comparisons, which, however, is rarely taken into the account by researches, leading to false results in many occasions. Moreover, the article examines robust statistical methods, particularly permutation tests and bootstrap. These methods combine robustness and high power. Finally, the study observes such issues as the completeness of results presentation and current debates about significance level, effect size and confidence intervals, reproducibility of psychological researches, and meta-analysis approach. Significance level has often been criticized; interval estimates and effect size were supposed to replace it. However, the problem of Null Hypothesis Significance Testing (NHST) has not been completely solved yet. A possible solution is presentation of complete data on research results including precise significance level, confidence intervals, effect size and etc. These estimations can be then applied in meta-analysis, which allows moving on to a new level of scientific generalizations.

Abstract 3789: Nessun Dorma : Have the Risks of Rosiglitazone been Exaggerated?

Circulation ◽  
2007 ◽  
Vol 116 (suppl_16) ◽  
Author(s):  
George A Diamond ◽  
Sanjay Kaul
Keyword(s):  
Confidence Intervals ◽  
Effect Size ◽  
Fixed Effects ◽  
Meta Analysis ◽  
Cardiovascular Death ◽  
Sensitivity Analyses ◽  
Odds Ratios ◽  
True Effect Size ◽  
Index Study ◽  
The Stability

Background A highly publicized meta-analysis of 42 clinical trials comprising 27,844 diabetics ignited a firestorm of controversy by charging that treatment with rosiglitazone was associated with a “…worrisome…” 43% greater risk of myocardial infarction ( p =0.03) and a 64% greater risk of cardiovascular death ( p =0.06). Objective The investigators excluded 4 trials from the infarction analysis and 19 trials from the mortality analysis in which no events were observed. We sought to determine if these exclusions biased the results. Methods We compared the index study to a Bayesian meta-analysis of the entire 42 trials (using odds ratio as the measure of effect size) and to fixed-effects and random-effects analyses with and without a continuity correction that adjusts for values of zero. Results The odds ratios and confidence intervals for the analyses are summarized in the Table . Odds ratios for infarction ranged from 1.43 to 1.22 and for death from 1.64 to 1.13. Corrected models resulted in substantially smaller odds ratios and narrower confidence intervals than did uncorrected models. Although corrected risks remain elevated, none are statistically significant (*p<0.05). Conclusions Given the fragility of the effect sizes and confidence intervals, the charge that roziglitazone increases the risk of adverse events is not supported by these additional analyses. The exaggerated values observed in the index study are likely the result of excluding the zero-event trials from analysis. Continuity adjustments mitigate this error and provide more consistent and reliable assessments of true effect size. Transparent sensitivity analyses should therefore be performed over a realistic range of the operative assumptions to verify the stability of such assessments especially when outcome events are rare. Given the relatively wide confidence intervals, additional data will be required to adjudicate these inconclusive results.

Meta-analysis of the impacts of water management on aquatic communities

2008 ◽  
Vol 65 (3) ◽  
pp. 437-447 ◽  
Author(s):  
Tim J Haxton ◽  
C Scott Findlay
Keyword(s):  
Water Management ◽  
Confidence Intervals ◽  
Effect Size ◽  
Meta Analysis ◽  
Ecological Impacts ◽  
Aquatic Communities ◽  
Flow Modification ◽  
Meta Analyses ◽  
Fail Safe ◽  
Habitat Generalists

Systematic meta-analyses were conducted on the ecological impacts of water management, including effects of (i) dewatering on macroinvertebrates, (ii) a hypolimnetic release on downstream aquatic fish and macro invertebrate communities, and (iii) flow modification on fluvial and habitat generalists. Our meta-analysis indicates, in general, that (i) macroinvertebrate abundance is lower in zones or areas that have been dewatered as a result of water fluctuations or low flows (overall effect size, –1.64; 95% confidence intervals (CIs), –2.51, –0.77), (ii) hypolimnetic draws are associated with reduced abundance of aquatic (fish and macroinvertebrates) communities (overall effect size, –0.84; 95% CIs, –1.38, –0.33) and macroinvertebrates (overall effect size, –0.73; 95% CIs, –1.24, –0.22) downstream of a dam, and (iii) altered flows are associated with reduced abundance of fluvial specialists (–0.42; 95% CIs, –0.81, –0.02) but not habitat generalists (overall effect size, –0.14; 95% CIs, –0.61, 0.32). Publication bias is evident in several of the meta-analyses; however, multiple experiments from a single study may be contributing to this bias. Fail-safe Ns suggest that many (>100) studies showing positive or no effects of water management on the selected endpoints would be required to qualitatively change the results of the meta-analysis, which in turn suggests that the conclusions are reasonably robust.

scholarly journals Confidence intervals for the overall effect size in random-effects meta-analysis.

2008 ◽  
Vol 13 (1) ◽  
pp. 31-48 ◽  
Author(s):  
Julio Sánchez-Meca ◽  
Fulgencio Marín-Martínez
Keyword(s):  
Confidence Intervals ◽  
Random Effects ◽  
Effect Size ◽  
Meta Analysis

scholarly journals Predictive physiological anticipatory activity preceding seemingly unpredictable stimuli: An update of Mossbridge et al’s meta-analysis

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 407 ◽  
Author(s):  
Michael Duggan ◽  
Patrizio Tressoldi
Keyword(s):  
Confidence Intervals ◽  
Publication Bias ◽  
Effect Size ◽  
Statistical Estimation ◽  
Meta Analysis ◽  
Weighted Mean ◽  
Weighted Effect Size ◽  
Credible Intervals ◽  
Weighted Effect ◽  
Anticipatory Activity

Background: This is an update of the Mossbridge et al’s meta-analysis related to the physiological anticipation preceding seemingly unpredictable stimuli which overall effect size was 0.21; 95% Confidence Intervals: 0.13 - 0.29 Methods: Nineteen new peer and non-peer reviewed studies completed from January 2008 to June 2018 were retrieved describing a total of 27 experiments and 36 associated effect sizes. Results: The overall weighted effect size, estimated with a frequentist multilevel random model, was: 0.28; 95% Confidence Intervals: 0.18-0.38; the overall weighted effect size, estimated with a multilevel Bayesian model, was: 0.28; 95% Credible Intervals: 0.18-0.38. The weighted mean estimate of the effect size of peer reviewed studies was higher than that of non-peer reviewed studies, but with overlapped confidence intervals: Peer reviewed: 0.36; 95% Confidence Intervals: 0.26-0.47; Non-Peer reviewed: 0.22; 95% Confidence Intervals: 0.05-0.39. Similarly, the weighted mean estimate of the effect size of Preregistered studies was higher than that of Non-Preregistered studies: Preregistered: 0.31; 95% Confidence Intervals: 0.18-0.45; No-Preregistered: 0.24; 95% Confidence Intervals: 0.08-0.41. The statistical estimation of the publication bias by using the Copas selection model suggest that the main findings are not contaminated by publication bias. Conclusions: In summary, with this update, the main findings reported in Mossbridge et al’s meta-analysis, are confirmed.

scholarly journals Introducere în metaanaliză. Metaanaliza corelațiilor

2020 ◽  
Vol 6 (2) ◽  
pp. 112-127
Author(s):  
Laurențiu Maricuțoiu
Keyword(s):  
Statistical Method ◽  
Confidence Intervals ◽  
Effect Size ◽  
Meta Analysis ◽  
Relevant Information ◽  
Effect Sizes ◽  
The Mean

The present paper discusses the fundamental principles of meta-analysis, as a statistical method for summarising results of correlational studies. We approach fundamental issues such as: the finality of meta-analysis and the problems associated with study artefacts. The paper also contains recommendations for: selecting the studies for meta-analysis, identifying the relevant information within these studies, computing mean effect sizes, confidence intervals and heterogeneity indexes of the mean effect size. Finally, we present indications for reporting meta-analysis results.

scholarly journals Predictive physiological anticipation preceding seemingly unpredictable stimuli: an update of Mossbridge’s et al. meta-analysis

2018 ◽  
Author(s):  
Michael Duggan ◽  
Patrizio Tressoldi
Keyword(s):  
Confidence Intervals ◽  
Effect Size ◽  
Bayesian Model ◽  
Statistical Estimation ◽  
Meta Analysis ◽  
Random Model ◽  
Weighted Mean ◽  
Weighted Effect Size ◽  
Credible Intervals ◽  
Weighted Effect

Background: This is an update of the Mossbridge et al’s meta-analysis related to the physiological anticipation preceding seemingly unpredictable stimuli which overall effect size was 0.21; 95% Confidence Intervals: 0.13 - 0.29Methods: Nineteen new peer and non-peer reviewed studies completed from January 2008 to June 2018 were retrieved describing a total of 27 experiments and 36 associated effect sizes.Results: The overall weighted effect size, estimated with a frequentist multilevel random model, was: 0.28; 95% Confidence Intervals: 0.18-0.38; the overall weighted effect size, estimated with a multilevel Bayesian model, was: 0.28; 95% Credible Intervals: 0.18-0.38. The weighted mean estimate of the effect size of peer reviewed studies was higher than that of non peer reviewed studies, but with overlapped confidence intervals: Peer reviewed: 0.36; 95% Confidence Intervals: 0.26-0.47; Non peer reviewed: 0.22; 95% Confidence Intervals: 0.05-0.39. Similarly, the weighted mean estimate of the effect size of Preregistered studies was higher than that of Non-Preregistered studies: Preregistered: 0.31; 95% Confidence Intervals: 0.18-0.45; No-Preregistered: 0.24; 95% Confidence Intervals: 0.08-0.41.The statistical estimation of the publication bias by using the Copas selection model suggest that the main findings are not contaminated by publication bias.Conclusions: In summary, with this update, the main findings reported in Mossbridge et al’s meta-analysis, are confirmed.

Appraising Research Reports

2016 ◽  
pp. 137-162
Author(s):  
John C. Norcross ◽  
Thomas P. Hogan ◽  
Gerald P. Koocher ◽  
Lauren A. Maggio
Keyword(s):  
Confidence Intervals ◽  
Publication Bias ◽  
Effect Size ◽  
Critical Appraisal ◽  
Meta Analysis ◽  
Flow Diagram ◽  
Careful Attention ◽  
Comparison Groups ◽  
Independent Variable ◽  
Meta Analyses

Assessing and interpreting research reports involves examination of individual studies as well as summaries of many studies. Summaries may be conveyed in narrative reviews or, more typically, in meta-analyses. This chapter reviews how researchers conduct a meta-analysis and report the results, especially by means of forest plots, which incorporate measures of effect size and their confidence intervals. A meta-analysis may also use moderator analyses or meta-regressions to identify important influences on the results. Critical appraisal of a study requires careful attention to the details of the sample used, the independent variable (treatment), dependent variable (outcome measure), the comparison groups, and the relation between the stated conclusions and the actual results. The CONSORT flow diagram provides a context for interpreting the sample and comparison groups. Finally, users must be alert to possible artifacts of publication bias.

scholarly journals Comparison of the power of statistical tests in connection with the discussion about the reproducibility criterion

2018 ◽  
Vol 15 (5) ◽  
pp. 4-14
Author(s):  
V. E. Osipov
Keyword(s):  
Effect Size ◽  
Statistical Tests ◽  
Meta Analysis ◽  
Statistical Significance ◽  
Mathematical Formulation ◽  
Random Component ◽  
Significance Level ◽  
Two Samples ◽  
Methodology Of Science ◽  
Typical Length

The criterion of reproducibility, as well as its functioning in post-non-classical science, are discussed in the Russian methodology of science. At the same time, critics avoid statistical calculations in their arguments. This raises the following questions: “What is reproducibility?” and “What is the mathematical formulation of the reproducibility criterion?” Literature review has identified five indicators of reproducibility, which was proposed by foreign colleagues. These indicators are being tested and discussed. However, there is no General mathematical formulation of the reproducibility criterion (an integral criterion covering these indicators), and these indicators have not yet become a standard. In the present work, we compare two statistical tests, related to one of these five indicators of reproducibility.Purpose of the study. The aim of this paper is to compare the powers of two tests of statistical significance that can be used to reveal the effect with the requirement of reproducibility of research results. In this case, the reproducibility is estimated by the indicator “significance”. In accordance with the first criterion, the effect is considered to be revealed if the effect size in all studies is significant (i.e. if the significance of the effect size is reproduced in all studies). In accordance with the second criterion, the effect is considered to be revealed if the weighted mean of the effect size obtained as a result of meta-analysis is significant (the significance of the effect size may be absent in individual studies).Materials and methods. Methods of mathematical statistics are used to achieve this goal. The powers of two tests are compared by two estimates. The first estimate is theoretical. The second one was obtained during a statistical experiment. The powers are calculated: 1) for different values of the Cohen’s effect size: “small”, “medium” and “large”, 2) for different degree of heterogeneity: zero (fixed-effect primary studies (from 2 to 8).Results. The power of the first test is less or much less than the power of the second one. The power of the first test decreases with the growth of the number of primary studies, and the power of the second one increases. Taking into account the conventional power value equal to 80%, the first criterion is unsuitable for use in the considered values of the parameters of primary studies (that is, if a two-tailed t-test with the significance level of 0.05 and with two samples of the typical length n=25 is used to determine the significance of the effect size in individual studies), while the power of the second test can be increased if necessary by increasing the number of primary studies included in the meta-analysis.Conclusion. If the criterion of reproducibility, known from the philosophy of science, is intended to confirm the existence of the effect (connection) or, in other words, to reveal the effect, in conditions where there is a significant random component in the measurement process, it is advisable to apply not the first, but the second test.

The Importance of Drawing Meaningful Conclusions from Data: A Review of the Literature with Meta-Analytic Inquiry

NASPA Journal ◽  
2004 ◽  
Vol 41 (3) ◽  
Author(s):  
David A. Walker
Keyword(s):  
Graduate Students ◽  
Confidence Intervals ◽  
Effect Size ◽  
Quantitative Research ◽  
Research Study ◽  
Meta Analysis ◽  
Review Of The Literature ◽  
Research Designs ◽  
Power Effect ◽  
Concept Usage

Using correct statistical concepts is an important component when conducting quantitative research. Ideas such as power, effect size, and confidence intervals need to be addressed appropriately every time a research study is initiated. The intent of this review of the literature is to reacquaint faculty, practitioners, and graduate students with scholarly information pertaining to these important concepts to facilitate improved implementation of quantitative research designs. Practical cases are interwoven within the review to furnish examples of concept importance, and a meta-analysis of concept usage found in articles published in the NASPA Journal is provided as a measure for implications.

scholarly journals Determining The Factors Affecting Fruit Hardness of Different Peach Types with Meta Analysis

2014 ◽  
Vol 3 (2) ◽  
pp. 98
Author(s):  
Hande Küçükönder ◽  
Kazım Kubilay Vursavuş ◽  
Fath Üçkardeş
Keyword(s):  
Effect Size ◽  
Contact Time ◽  
Impact Force ◽  
Meta Analysis ◽  
Theory Of Elasticity ◽  
Shock Acceleration ◽  
Significance Level ◽  
The Mean ◽  
The Impact ◽  
The Relationship

The aim of this study is to determine the factor effective in determining the hardness of Caterina, Suidring, Royal Glory and Tirrenia peach types using meta analysis. In the study, the impact force (Fi) and the contact time (tc) were detected and the impulse values (I) that are expressed as independent variable in the area under the curve were calculated in the measurements performed using the technique of a low-mass lateral impactor multiplicated with peach. Using the theory of elasticity, the independent variables were determined as Fmax (maximum impact force), contact time (tmax), Fmax/tmax, 1/tmax, 1/tmax2,5, Fmax/tmax 1.25 and Fmax2.5 parameters. The correlation coefficient values showing the relationship between these parameters and the dependent variable Magness-Taylor force (MT) were calculated and were combined with meta-analysis by using the Hunter-Schmid and Fisher’s Z methods. The Cohen’s classification criterion was used in evaluating the resulting mean effect size (combined correlation value) and in determining its direction. As a result of the meta-analysis, the mean effect size according to Hunter-Schmid method was found 0.436 (0.371-0.497) positively directed in 95% confidence interval, while it was found 0.468 (0.390-0.545) according to Fisher’s Z method. The effect sizes in both methods were determined “mid-level” according to the Cohen’s classification. When the significance level of the studies was analyzed with the Z test, all of the ones that taken into the meta analysis has been found statistically significant. As a result of the meta analysis in this study evaluating the relationship of peach types with the fruit hardness, the mean effect size has been found to reach “strong level”. Consequently, “maximum shock acceleration” was found to be a more effective factor comparing to the other factors in determining the the fruit hardness according to the results of meta analysis applied in both methods.

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