scholarly journals Finding domain-general metacognitive mechanisms requires using appropriate tasks

2017 ◽  
Author(s):  
Eugene Ruby ◽  
Nathan Giles ◽  
Hakwan Lau
Keyword(s):  
Visual Perception ◽  
Sample Size ◽  
False Positive ◽  
Statistical Power ◽  
Forced Choice ◽  
The Other ◽  
Online Experiments ◽  
Positive Correlation ◽  
Domain Specific ◽  
Unresolved Question

AbstractAn important yet unresolved question is whether or not metacognition consists of domain-general or domain-specific mechanisms. While most studies on this topic suggest a dissociation between metacognitive abilities at the neural level, there are conflicting reports at the behavioral level. Specifically, while McCurdy et al. (2013) found a positive correlation between metacognitive efficiency for visual perception and memory, Baird et al. (2013) didn’t find this correlation. One possible explanation for this disparity is that the former included two-alternative-forced choice (2AFC) judgments in both their visual and memory tasks, whereas the latter used 2AFC for one task and yes/no (YN) judgments for the other. In support of this hypothesis, we ran two online experiments meant to mirror McCurdy et al. (2013) and Baird et al. (2013) with considerable statistical power (n=100), and replicated the main findings of both studies. This suggests the finding of McCurdy et al (2013) was not a ‘fluke’ (i.e. false positive). In a third experiment with the same sample size, which included YN judgments for both tasks, we did not find a correlation between metacognitive functions, suggesting that the conflict between McCurdy et al. (2013) and Baird et al. (2013) stemmed from the use of YN judgments in the latter study. Our results underscore the need to avoid conflating 2AFC and YN judgments, which is a common problem.

scholarly journals Crowdsourcing visual perception experiments: a case of contrast threshold

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e8339 ◽  
Author(s):  
Kyoshiro Sasaki ◽  
Yuki Yamada
Keyword(s):  
Visual Perception ◽  
Laboratory Experiment ◽  
Psychological Research ◽  
Small Sample ◽  
The Other ◽  
Contrast Threshold ◽  
Repetition Condition ◽  
Experimental Conditions ◽  
Online Experiments ◽  
Contrast Thresholds

Crowdsourcing has commonly been used for psychological research but not for studies on sensory perception. A reason is that in online experiments, one cannot ensure that the rigorous settings required for the experimental environment are replicated. The present study examined the suitability of online experiments on basic visual perception, particularly the contrast threshold. We conducted similar visual experiments in the laboratory and online, employing three experimental conditions. The first was a laboratory experiment, where a small sample of participants (n = 24; laboratory condition) completed a task with 10 iterations. The other two conditions were online experiments: participants were either presented with a task without repetition of trials (n = 285; online non-repetition condition) or one with 10 iterations (n = 166; online repetition condition). The results showed significant equivalence in the contrast thresholds between the laboratory and online repetition conditions, although a substantial amount of data needed to be excluded from the analyses in the latter condition. The contrast threshold was significantly higher in the online non-repetition condition compared with the laboratory and online repetition conditions. To make crowdsourcing more suitable for investigating the contrast threshold, ways to reduce data wastage need to be formulated.

scholarly journals Data Analysis and Power Simulations with General Linear Mixed Modelling for Psychophysical Data – A Practical, R-Based Guide

2021 ◽  
Author(s):  
Björn Jörges
Keyword(s):  
Data Analysis ◽  
Sample Size ◽  
Statistical Power ◽  
Statistical Tests ◽  
Forced Choice ◽  
Choice Data ◽  
Psychophysical Data ◽  
Statistical Validity ◽  
Sample Size Planning ◽  
Mixed Modelling

Sample size planning is not straight-forward for the complex designs that are usually employed in psychophysical (two-alternative forced-choice) experiments: characteristics such as binary response variables and nested data structures where responses may be correlated differently within participants and experimental sessions than across participants and experimental sessions make it harder to estimate the necessary number of participants and trials with traditional means. In this practical R-based guide, we first show in detail how we can simulate verisimilar psychophysical data. We then use these simulations to compare two different methods by which two-alternative forced-choice data can be analyzed: (1) the “two-step” approach, where first psychometric functions are fitted and then statistical tests are performed over the parameters of these fitted psychometric functions; (2) an approach based on Generalized Linear Mixed Modeling (GLMM) that does not require the intermediary step of fitting psychometric functions. We argue that the GLMM approach enhances statistical validity and show that it can increase statistical power. Finally, we provide a sample implementation of a simulation-based power analysis that can be used as-is for many simple designs, but is also easily adaptable for more complex designs. Overall, we show that a GLMM-based approach can be beneficial for data analysis and sample size planning for typical (two-alternative forced-choice) psychophysical designs.

Relationship amongst ResearchGate altmetric indicators and Scopus bibliometric indicators

2015 ◽  
Vol 116 (9/10) ◽  
pp. 564-577 ◽  
Author(s):  
RISHABH SHRIVASTAVA ◽  
Preeti Mahajan
Keyword(s):  
Sample Size ◽  
Correlation Coefficients ◽  
Strong Positive Correlation ◽  
Bibliometric Indicators ◽  
Pearson’S Correlation ◽  
Content Type ◽  
Positive Correlation ◽  
Pearson's Correlation ◽  
Different Characteristics ◽  
The Relationship

Purpose – The purpose of this paper is twofold. First, the study aims to investigate the relationship between the altmetric indicators from ResearchGate (RG) and the bibliometric indicators from the Scopus database. Second, the study seeks to examine the relationship amongst the RG altmetric indicators themselves. RG is a rich source of altmetric indicators such as Citations, RGScore, Impact Points, Profile Views, Publication Views, etc. Design/methodology/approach – For establishing whether RG metrics showed the same results as the established sources of metrics, Pearson’s correlation coefficients were calculated between the metrics provided by RG and the metrics obtained from Scopus. Pearson’s correlation coefficients were also calculated for the metrics provided by RG. The data were collected by visiting the profile pages of all the members who had an account in RG under the Department of Physics, Panjab University, Chandigarh (India). Findings – The study showed that most of the RG metrics showed strong positive correlation with the Scopus metrics, except for RGScore (RG) and Citations (Scopus), which showed moderate positive correlation. It was also found that the RG metrics showed moderate to strong positive correlation amongst each other. Research limitations/implications – The limitation of this study is that more and more scientists and researchers may join RG in the future, therefore the data may change. The study focuses on the members who had an account in RG under the Department of Physics, Panjab University, Chandigarh (India). Perhaps further studies can be conducted by increasing the sample size and by taking a different sample size having different characteristics. Originality/value – Being an emerging field, not much has been conducted in the area of altmetrics. Very few studies have been conducted on the reach of academic social networks like RG and their validity as sources of altmetric indicators like RGScore, Impact Points, etc. The findings offer insights to the question whether RG can be used as an alternative to traditional sources of bibliometric indicators, especially with reference to a rapidly developing country such as India.

P1-188: Enrichment strategies for secondary prevention trials: The effect of restrictive inclusion criteria on statistical power and sample size

2008 ◽  
Vol 4 ◽  
pp. T263-T264
Author(s):  
Steven D. Edland ◽  
Linda K. McEvoy ◽  
Dominic Holland ◽  
John C. Roddey ◽  
Christine Fennema-Notestine ◽  
...  
Keyword(s):  
Secondary Prevention ◽  
Sample Size ◽  
Statistical Power ◽  
Inclusion Criteria ◽  
Prevention Trials

SERUM GONADOTROPHINS, TESTOSTERONE AND SPERMATOGENESIS IN SUBFERTILE MEN

1977 ◽  
Vol 86 (3) ◽  
pp. 651-658 ◽  
Author(s):  
J. H. Aafjes ◽  
J. C. M. van der Vijver ◽  
R. Docter ◽  
P. E. Schenck
Keyword(s):  
Partial Correlation ◽  
Sperm Count ◽  
Correlation Coefficients ◽  
Serum Levels ◽  
Significant Negative Correlation ◽  
The Other ◽  
Sperm Production ◽  
Positive Correlation ◽  
Natural Logarithm ◽  
Biopsy Score

ABSTRACT In 210 subfertile men there existed a significant positive correlation between serum FSH and LH (0.41). No correlation was observed between the gonadotrophin levels and testosterone. In contrast to this FSH as well as LH were negatively correlated with the natural logarithm (In) of the sperm count/ml ejaculate (−0.44 and −0.18, respectively). When the positive correlation which existed between FSH and LH was used to calculate partial correlation coefficients, the coefficient between FSH and ln sperm count did hardly change (−0.41) the coefficient between LH and ln sperm count on the other hand became insignificant (−0.05). This suggests that spermatogenesis influences FSH serum levels in subfertile men by a decreased suppression when sperm production is diminished. Testicular biopsies taken from 97 of these patients were used to determine biopsy scores. These scores showed a significant negative correlation with FSH (−0.34) and a positive one with ln sperm count/ml ejaculate (0.45). Interestingly the biopsy score of 16 patients who fertilized their wives, was found to be higher compared with the score of the other patients who did not fertilize. The number of sperm/ml ejaculate and the FSH values of these 2 groups of biopsied patients were, however, not significantly different. This leads to the conclusion that the biopsy score is a better parameter for the evaluation of oligospermic men than either sperm count or FSH serum values.

Statistical Power Analysis can Improve Fisheries Research and Management

1990 ◽  
Vol 47 (1) ◽  
pp. 2-15 ◽  
Author(s):  
Randall M. Peterman
Keyword(s):  
Sample Size ◽  
Power Analysis ◽  
Statistical Power ◽  
Small Sample Size ◽  
Industrial Effluent ◽  
Small Sample ◽  
Detectable Effect ◽  
Type Ii ◽  
Sampling Variability ◽  
Statistical Power Analysis

Ninety-eight percent of recently surveyed papers in fisheries and aquatic sciences that did not reject some null hypothesis (H0) failed to report β, the probability of making a type II error (not rejecting H0 when it should have been), or statistical power (1 – β). However, 52% of those papers drew conclusions as if H0 were true. A false H0 could have been missed because of a low-power experiment, caused by small sample size or large sampling variability. Costs of type II errors can be large (for example, for cases that fail to detect harmful effects of some industrial effluent or a significant effect of fishing on stock depletion). Past statistical power analyses show that abundance estimation techniques usually have high β and that only large effects are detectable. I review relationships among β, power, detectable effect size, sample size, and sampling variability. I show how statistical power analysis can help interpret past results and improve designs of future experiments, impact assessments, and management regulations. I make recommendations for researchers and decision makers, including routine application of power analysis, more cautious management, and reversal of the burden of proof to put it on industry, not management agencies.

Morpho-Biochemical Characteristics of Brinjal Germplasms Affect the Abundance And Infestation of Jassid

2021 ◽  
Vol 19 (1) ◽  
pp. 81-91
Author(s):  
F Yasmin ◽  
MR Amin ◽  
M Afroz ◽  
MAH Swapon ◽  
MM Hossain
Keyword(s):  
Protein Content ◽  
Chlorophyll Content ◽  
Negative Correlation ◽  
Significant Positive Correlation ◽  
Significant Negative Correlation ◽  
Reducing Sugar ◽  
Total Sugar ◽  
The Other ◽  
Biochemical Characteristics ◽  
Positive Correlation

The tropical vegetable, brinjal is cultivated throughout the year in Bangladesh but the crop is infested by a number of insects including jassid. This study investigated the effects of different biophysical and biochemical characteristics of twelve brinjal germplasms on the abundance and infestation of jassid. The experiment was conducted during September 2018 to March 2019 in Gazipur, Bangladesh with twelve brinjal germplasms namely BD-7320, BD-7328, BD-9952, BD-10154, BD-10158, BARI Begun-1, BARI Begun-4, BARI Begun-5, BARI Begun- 6, BARI Begun-7, BARI Begun-8 and BARI Begun-9. The incidence of jassid was recorded from 3rd December to 26th March, and the lowest population was found on BARI Begun- 6. Among the biophysical traits, plant height, number of branch and leaf per plant, and leaf area exerted significant positive correlation; whereas trichome on lower and upper surfaces of leaf, spine per stem and leaf showed significant negative correlation with the abundance of jassid. On the other hand, moisture, reducing sugar, total sugar and protein content of the leaves and fruits, chlorophyll content of the leaves exerts significant positive correlation but ash and pH contents of the leaves and fruits were negatively correlated with the abundance of jassid. Jassids showed the lowest level of leaf infestation on BARI Begun-6, which could be for further analysis to develop jassid resistant brinjal. SAARC J. Agric., 19(1): 81-91 (2021)

DS-kNN

2021 ◽  
Vol 15 (2) ◽  
pp. 131-144
Author(s):  
Redha Taguelmimt ◽  
Rachid Beghdad
Keyword(s):  
Intrusion Detection ◽  
False Positive ◽  
Detection Rate ◽  
Nearest Neighbors ◽  
The Other ◽  
Intrusion Detection Systems ◽  
K Nearest Neighbors ◽  
Detection Systems ◽  
Knn Classifier ◽  
Better Than

On one hand, there are many proposed intrusion detection systems (IDSs) in the literature. On the other hand, many studies try to deduce the important features that can best detect attacks. This paper presents a new and an easy-to-implement approach to intrusion detection, named distance sum-based k-nearest neighbors (DS-kNN), which is an improved version of k-NN classifier. Given a data sample to classify, DS-kNN computes the distance sum of the k-nearest neighbors of the data sample in each of the possible classes of the dataset. Then, the data sample is assigned to the class having the smallest sum. The experimental results show that the DS-kNN classifier performs better than the original k-NN algorithm in terms of accuracy, detection rate, false positive, and attacks classification. The authors mainly compare DS-kNN to CANN, but also to SVM, S-NDAE, and DBN. The obtained results also show that the approach is very competitive.

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