Supplemental Material for Bootstrapping to Test for Nonzero Population Correlation Coefficients Using Univariate Sampling

The analysis of student performance involves data modelling that enables the formulation of hypotheses and insights about student behaviour and personality. We extract online behaviours as proxies to Extraversion and Conscientiousness, which have been proven to correlate with academic performance. The proxies of personalities we obtain yield significant (p<0.05) population correlation coefficients for traits against grade—0.846 for Extraversion and 0.319 for Conscientiousness. Furthermore, we demonstrate that a student’s e-behaviour and personality can be used with deep learning (LSTM) to predict and forecast whether a student is at risk of failing the year. Machine learning procedures followed in this report provide a methodology to timeously identify students who are likely to become at risk of poor academic performance. Using engineered online behaviour and personality features, we obtain a classification accuracy (κ) of students at risk of 0.51. Lastly, we show that we can design an intervention process using machine learning that supplements the existing performance analysis and intervention methods. The methodology presented in this article provides metrics that measure the factors that affect student performance and complement the existing performance evaluation and intervention systems in education.

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Correlation and Regression using VASSARSTATS

IRA International Journal of Education and Multidisciplinary Studies ◽

10.21013/jems.v3.n2.p7 ◽

2016 ◽

Vol 3 (2) ◽

Author(s):

Suma AP ◽

KP Suresh

Keyword(s):

Correlation Coefficient ◽

Partial Correlation ◽

Rank Order ◽

Correlation Coefficients ◽

Regression Coefficients ◽

Multiple Correlation ◽

Population Correlation ◽

Coefficient Corrélation ◽

Sample Correlation ◽

Simple Logistic

In a bivariate or a multivariate data, to understand the association between the variables Correlation is the best tool. It gives the degree of relationship between the variables. Regression gives the exact linear relationship between the variables. This article gives details of capabilities of Vassarstats Correlation and Regression and procedure to calculate Correlation coefficient and Regression coefficients with examples. Vassarstats Correlation and Regression can perform Linear Correlation and Regression, Intercorrelations, Multiple Correlation and Regression, Partial Correlation, 0.95 and 0.99 Confidence intervals for population correlation coefficient, Estimating the Population Value of rho, Significance of value of r, Significance of difference between two correlation coefficients, Significance of difference between sample correlation coefficient and hypothetical value of population Correlation coefficient, Rank Order Correlation, Correlation coefficient for a 2*2 contingency table, Point biserial correlation coefficient, Correlation for unordered pairs, and then Simple Logistic Regression.

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A procedure for combining sample correlation coefficients and vote counts to obtain an estimate and a confidence interval for the population correlation coefficient.

Psychological Bulletin ◽

10.1037/0033-2909.117.3.530 ◽

1995 ◽

Vol 117 (3) ◽

pp. 530-546 ◽

Cited By ~ 10

Author(s):

Brad J. Bushman ◽

Morgan C. Wang

Keyword(s):

Confidence Interval ◽

Correlation Coefficient ◽

Correlation Coefficients ◽

Population Correlation ◽

Sample Correlation

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Bootstrapping to test for nonzero population correlation coefficients using univariate sampling.

Psychological Methods ◽

10.1037/1082-989x.12.4.414 ◽

2007 ◽

Vol 12 (4) ◽

pp. 414-433 ◽

Cited By ~ 19

Author(s):

William Howard Beasley ◽

Lise DeShea ◽

Larry E. Toothaker ◽

Jorge L. Mendoza ◽

David E. Bard ◽

...

Keyword(s):

Correlation Coefficients ◽

Population Correlation

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Reliability of the Minimum Masking Level as Outcome Variable in Tinnitus Clinical Research

American Journal of Audiology ◽

10.1044/2020_aja-20-00047 ◽

2020 ◽

Vol 29 (3) ◽

pp. 429-435

Author(s):

Patricia C. Mancini ◽

Richard S. Tyler ◽

Hyung Jin Jun ◽

Tang-Chuan Wang ◽

Helena Ji ◽

...

Keyword(s):

Standard Deviation ◽

High Frequency ◽

Pearson Correlation ◽

Correlation Coefficients ◽

Outcome Variable ◽

Reliable Estimate ◽

Moderate Correlation ◽

Trained Subjects ◽

The Relationship ◽

Minimum Intensity

Purpose The minimum masking level (MML) is the minimum intensity of a stimulus required to just totally mask the tinnitus. Treatments aimed at reducing the tinnitus itself should attempt to measure the magnitude of the tinnitus. The objective of this study was to evaluate the reliability of the MML. Method Sample consisted of 59 tinnitus patients who reported stable tinnitus. We obtained MML measures on two visits, separated by about 2–3 weeks. We used two noise types: speech-shaped noise and high-frequency emphasis noise. We also investigated the relationship between the MML and tinnitus loudness estimates and the Tinnitus Handicap Questionnaire (THQ). Results There were differences across the different noise types. The within-session standard deviation averaged across subjects varied between 1.3 and 1.8 dB. Across the two sessions, the Pearson correlation coefficients, range was r = .84. There was a weak relationship between the dB SL MML and loudness, and between the MML and the THQ. A moderate correlation ( r = .44) was found between the THQ and loudness estimates. Conclusions We conclude that the dB SL MML can be a reliable estimate of tinnitus magnitude, with expected standard deviations in trained subjects of about 1.5 dB. It appears that the dB SL MML and loudness estimates are not closely related.

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Clausal Density Between Ages 4 and 9 Years for the Edmonton Narrative Norms Instrument: Reference Data and Psychometric Properties

Language Speech and Hearing Services in Schools ◽

10.1044/2020_lshss-20-00043 ◽

2020 ◽

pp. 1-15

Author(s):

Ling-Yu Guo ◽

Phyllis Schneider ◽

William Harrison

Keyword(s):

Diagnostic Accuracy ◽

Psychometric Properties ◽

Language Impairment ◽

Reference Data ◽

Reliability And Validity ◽

Correlation Coefficients ◽

Criterion Validity ◽

Likelihood Ratios ◽

Generation Task ◽

Sensitivity Specificity

Purpose This study provided reference data and examined psychometric properties for clausal density (CD; i.e., number of clauses per utterance) in children between ages 4 and 9 years from the database of the Edmonton Narrative Norms Instrument (ENNI). Method Participants in the ENNI database included 300 children with typical language (TL) and 77 children with language impairment (LI) between the ages of 4;0 (years;months) and 9;11. Narrative samples were collected using a story generation task, in which children were asked to tell stories based on six picture sequences. CD was computed from the narrative samples. The split-half reliability, concurrent criterion validity, and diagnostic accuracy were evaluated for CD by age. Results CD scores increased significantly between ages 4 and 9 years in children with TL and those with LI. Children with TL produced higher CD scores than those with LI at each age level. In addition, the correlation coefficients for the split-half reliability and concurrent criterion validity of CD scores were all significant at each age level, with the magnitude ranging from small to large. The diagnostic accuracy of CD scores, as revealed by sensitivity, specificity, and likelihood ratios, was poor. Conclusions The finding on diagnostic accuracy did not support the use of CD for identifying children with LI between ages 4 and 9 years. However, given the attested reliability and validity for CD, reference data of CD from the ENNI database can be used for evaluating children's difficulties with complex syntax and monitoring their change over time. Supplemental Material https://doi.org/10.23641/asha.13172129

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Interobserver Reliability Using the Phonetic Level Evaluation With Severely and Profoundly Hearing-Impaired Children

Journal of Speech Language and Hearing Research ◽

10.1044/jshr.3405.989 ◽

1991 ◽

Vol 34 (5) ◽

pp. 989-999 ◽

Cited By ~ 6

Author(s):

Stephanie Shaw ◽

Truman E. Coggins

Keyword(s):

Interrater Reliability ◽

Interobserver Reliability ◽

Intraclass Correlation ◽

Correlation Coefficients ◽

Hearing Impaired ◽

Intraclass Correlation Coefficients ◽

Assessment Measure ◽

Impaired Children ◽

Speech Assessment ◽

Hearing Impaired Children

This study examines whether observers reliably categorize selected speech production behaviors in hearing-impaired children. A group of experienced speech-language pathologists was trained to score the elicited imitations of 5 profoundly and 5 severely hearing-impaired subjects using the Phonetic Level Evaluation (Ling, 1976). Interrater reliability was calculated using intraclass correlation coefficients. Overall, the magnitude of the coefficients was found to be considerably below what would be accepted in published behavioral research. Failure to obtain acceptably high levels of reliability suggests that the Phonetic Level Evaluation may not yet be an accurate and objective speech assessment measure for hearing-impaired children.

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