A simplified approach to bias estimation for correlations

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Xiaofeng Steven Liu
Keyword(s):  
Partial Correlation ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Small Sample ◽  
Bias Estimation ◽  
Simplified Approach ◽  
Parametric Bootstrapping ◽  
Sample Data ◽  
Distributional Assumptions ◽  
Non Parametric

Abstract Objectives We introduce a simple and unified methodology to estimate the bias of Pearson correlation coefficients, partial correlation coefficients, and semi-partial correlation coefficients. Methods Our methodology features non-parametric bootstrapping and can accommodate small sample data without making any distributional assumptions. Results Two examples with R code are provided to illustrate the computation. Conclusions The computation strategy is easy to implement and remains the same, be it Pearson correlation or partial or semi-partial correlation.

scholarly journals Correlation Coefficients for a Study with Repeated Measures

2020 ◽  
Vol 2020 ◽  
pp. 1-11 ◽  
Author(s):  
Guogen Shan ◽  
Hua Zhang ◽  
Tao Jiang
Keyword(s):  
Repeated Measures ◽  
Partial Correlation ◽  
Mixed Model ◽  
Mean Squared Error ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Mixed Effects ◽  
Repeated Measure ◽  
Cross Sectional ◽  
Mixed Model Approach

Repeated measures are increasingly collected in a study to investigate the trajectory of measures over time. One of the first research questions is to determine the correlation between two measures. The following five methods for correlation calculation are compared: (1) Pearson correlation; (2) correlation of subject means; (3) partial correlation for subject effect; (4) partial correlation for visit effect; and (5) a mixed model approach. Pearson correlation coefficient is traditionally used in a cross-sectional study. Pearson correlation is close to the correlations computed from mixed-effects models that consider the correlation structure, but Pearson correlation may not be theoretically appropriate in a repeated-measure study as it ignores the correlation of the outcomes from multiple visits within the same subject. We compare these methods with regard to the average of correlation and the mean squared error. In general, correlation under the mixed-effects model with the compound symmetric structure is recommended as its correlation is close to the nominal level with small mean square error.

Comparison of ocular biometric parameters between concomitant exotropic and orthotropic eyes

2020 ◽  
Author(s):  
Weifen Gong ◽  
Fan Yang ◽  
Shibin Lin ◽  
Geng Wang
Keyword(s):  
Strong Correlation ◽  
Partial Correlation ◽  
Pearson Correlation ◽  
Corneal Thickness ◽  
Anterior Chamber Depth ◽  
Correlation Coefficients ◽  
Cross Sectional Study ◽  
Spherical Equivalent ◽  
Cross Sectional ◽  
Cover Test

Abstract PurposeTo compare the biometric characteristics between concomitant exotropia (XT) and orthotropia (OT) with OA2000.MethodThis cross-sectional study collected 4–18 years old children. All subjects underwent a comprehensive ophthalmic examination and prism alternate cover test for ocular alignment measurement. Included subjects had no any eye surgery, structural ocular anomalies, amblyopia of either eyes, ptosis, cataract and nystagmus. OA-2000 was used for the measurement of ocular biological parameters. Spherical equivalent (SE, spherical power + (cylindrical power)/2), keratometry, central corneal thickness (CCT), white to white distance (WTW), pupil diameter (PD), anterior chamber depth (ACD), lens thickness (LT), axial lengths (AL) and intereye differences in SE, keratometry, CCT, WTW, PD, ACD, LT and AL were analyzed by independent sample t-tests. Pearson correlation was used for correlations assessment. Partial correlation was used to control for intereye differences in SE.ResultsA total of 156 subjects (79 XT and 77 OT) were collected. Intereye differences in spherical equivalent (SE) (t 2.369, P 0.019), AL (t 3.423, P 0.001), ACD (t 3.782, P < 0.001), LT (t 3.136, P 0.002) and PD (t 3.229, P 0.002) were significantly larger in XT patients than OT patients. The correlation coefficient of XT with SE asymmetry was 0.187 (P 0.020), 0.265 with AL asymmetry (P 0.001), 0.289 with ACD asymmetry (P < 0.001), 0.251 with PD asymmetry (P 0.002) and 0.243 with LT asymmetry (P 0.002). Strong correlation (r 0.875) was found between anisometropia and AL asymmetry. After controlling the effect of anisometropia, the correlation coefficients slightly reduced between XT patients and intereye differences in AL (reduced to 0.213), ACD (reduced to 0.266), PD (reduced to 0.230) and LT (reduced to 0.230). Strong correlation (r 0.855) was found between intereye differences in ACD and LT.ConclusionCompared with OT subjects, intereye differences in SE, AL, ACD, LT and PD were significantly larger in XT patients and had positive correlation with XT and may be associated with the pathogenesis of XT.

scholarly journals A Stepwise Approach for High-Dimensional Gaussian Graphical Models

2021 ◽  
Vol 1 (2) ◽  
Author(s):  
Ruben Zamar ◽  
Marcelo Ruiz ◽  
Ginette Lafit ◽  
Javier Nogales
Keyword(s):  
Graphical Models ◽  
Partial Correlation ◽  
Pearson Correlation ◽  
Real Life ◽  
Correlation Coefficients ◽  
High Dimensional ◽  
Prediction Errors ◽  
Gaussian Graphical Models ◽  
Stepwise Approach ◽  
Linear Predictors

We present a stepwise approach to estimate high dimensional Gaussian graphical models. We exploit the relation between the partial correlation coefficients and the distribution of the prediction errors, and parametrize the model in terms of the Pearson correlation coefficients between the prediction errors of the nodes’ best linear predictors. We propose a novel stepwise algorithm for detecting pairs of conditionally dependent variables. We compare the proposed algorithm with existing methods including graphical lasso (Glasso), constrained `l1-minimization(CLIME) and equivalent partial correlation (EPC), via simulation studies and real life applications. In our simulation study we consider several model settings and report the results using different performance measures that look at desirable features of the recovered graph.

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

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.

Comparative Responses to Squats Completed with Free Weights and an Exoskeleton

2020 ◽  
Vol 4 (1) ◽  
pp. 51-63
Author(s):  
Peter Neuhaus ◽  
Chris Jumonville ◽  
Rachel A. Perry ◽  
Roman Edwards ◽  
Jake L. Martin ◽  
...  
Keyword(s):  
Data Collection ◽  
Female Athletes ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Actual Data ◽  
Limited Data ◽  
Comparative Similarity ◽  
Insufficient Amount ◽  
Force Data ◽  
Familiarization Session

AbstractTo assess the comparative similarity of squat data collected as they wore a robotic exoskeleton, female athletes (n=14) did two exercise bouts spaced 14 days apart. Data from their exoskeleton workout was compared to a session they did with free weights. Each squat workout entailed a four-set, four-repetition paradigm with 60-second rest periods. Sets for each workout involved progressively heavier (22.5, 34, 45.5, 57 kg) loads. The same physiological, perceptual, and exercise performance dependent variables were measured and collected from both workouts. Per dependent variable, Pearson correlation coefficients, t-tests, and Cohen's d effect size compared the degree of similarity between values obtained from the exoskeleton and free weight workouts. Results show peak O2, heart rate, and peak force data produced the least variability. In contrast, far more inter-workout variability was noted for peak velocity, peak power, and electromyography (EMG) values. Overall, an insufficient amount of comparative similarity exists for data collected from both workouts. Due to the limited data similarity, the exoskeleton does not exhibit an acceptable degree of validity. Likely the cause for the limited similarity was due to the brief amount of familiarization subjects had to the exoskeleton prior to actual data collection. A familiarization session that accustomed subjects to squats done with the exoskeleton prior to actual data collection may have considerably improved the validity of data obtained from that device.

Leader-Member Exchange (LMX) Impact on Work-Home Interference in a South African Commuter Transport Engineering Company

2019 ◽  
Vol 43 ◽  
Author(s):  
Jan Christoff Visagie ◽  
Michael M. Jones ◽  
Herman L. Linde
Keyword(s):  
South African ◽  
Structural Equation ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Leader Member Exchange ◽  
Negative Consequences ◽  
Dyadic Relationship ◽  
Cross Sectional ◽  
Engineering Company ◽  
Member Exchange

The South African workplace is confronted with many leadership challenges, specifically those relating to the employment relationship between subordinates and their supervisors. A high-quality relationship is essential, considering the work-family spillovers employees experience. Limited research has been conducted on the potential positive and negative consequences of the leader-member exchange (LMX) dyadic relationship. In this study, we used a cross-sectional research design, and drew an employee sample (N = 120) from a commuter transport engineering company. A five-point Likert scale was employed and statistical analyses were carried out using the SAS statistical program. We calculated Pearson correlation coefficients and used structural equation modelling to test the proposed conceptual model to indicate possible correlations between the different variables. The main finding of the study was that the nature of the LMX relationship quality in the relevant company appeared to be high and positively related to work-home enrichment but negatively related to work-home conflict and role overload. The article concludes by making a number of suggestions to respond to challenges.

Bioinformatics Study on Serum Triglyceride Levels for Analysis of a Potential Risk Factor Affecting Blood Pressure Variability

2019 ◽  
Vol 14 (5) ◽  
pp. 376-385 ◽  
Author(s):  
Lin Xu ◽  
Jiangming Huang ◽  
Zhe Zhang ◽  
Jian Qiu ◽  
Yan Guo ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Systolic Blood Pressure ◽  
Blood Pressure Variability ◽  
Partial Correlation ◽  
Pearson Correlation ◽  
Target Organ Damage ◽  
Serum Triglyceride ◽  
Hypertensive Patients ◽  
Group A ◽  
Group B

Objective: The purpose of this study was to establish whether Triglycerides (TGs) are related to Blood Pressure (BP) variability and whether controlling TG levels leads to better BP variability management and prevents Cardiovascular Disease (CVD). Methods: In this study, we enrolled 106 hypertensive patients and 80 non-hypertensive patients. Pearson correlation and partial correlation analyses were used to define the relationships between TG levels and BP variability in all subjects. Patients with hypertension were divided into two subgroups according to TG level: Group A (TG<1.7 mmol/L) and Group B (TG>=1.7 mmol/L). The heterogeneity between the two subgroups was compared using t tests and covariance analysis. Results: TG levels and BP variability were significantly different between the hypertensive and non-hypertensive patients. Two-tailed Pearson correlation tests showed that TG levels are positively associated with many BP variability measures in all subjects. After reducing other confounding factors, the partial correlation analysis revealed that TG levels are still related to the Standard Deviation (SD), Coefficient of Variation (CV) of nighttime systolic blood pressure and CV of nighttime diastolic blood pressure, respectively (each p<0.05). In the subgroups, group A had a lower SD of nighttime Systolic Blood Pressure (SBP_night_SD; 11.39±3.80 and 13.39±4.16, p=0.011), CV of nighttime systolic blood pressure (SBP_night_CV; 0.09±0.03 and 0.11±0.03, p=0.014) and average real variability of nighttime systolic blood pressure (SBP_night_ARV; 10.99±3.98 and 12.6±3.95, p=0.024) compared with group B, even after adjusting for age and other lipid indicators. Conclusion: TG levels are significantly associated with BP variability and hypertriglyceridemia, which affects blood pressure variability before causing target organ damage.

Enhanced context-aware recommendation using topic modeling and particle swarm optimization

2021 ◽  
pp. 1-16
Author(s):  
Ibtissem Gasmi ◽  
Mohamed Walid Azizi ◽  
Hassina Seridi-Bouchelaghem ◽  
Nabiha Azizi ◽  
Samir Brahim Belhaouari
Keyword(s):  
Topic Modeling ◽  
Latent Dirichlet Allocation ◽  
State Of The Art ◽  
Weighting Function ◽  
Contextual Factors ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Pso Algorithm ◽  
Context Aware ◽  
Proposed Model

Context-Aware Recommender System (CARS) suggests more relevant services by adapting them to the user’s specific context situation. Nevertheless, the use of many contextual factors can increase data sparsity while few context parameters fail to introduce the contextual effects in recommendations. Moreover, several CARSs are based on similarity algorithms, such as cosine and Pearson correlation coefficients. These methods are not very effective in the sparse datasets. This paper presents a context-aware model to integrate contextual factors into prediction process when there are insufficient co-rated items. The proposed algorithm uses Latent Dirichlet Allocation (LDA) to learn the latent interests of users from the textual descriptions of items. Then, it integrates both the explicit contextual factors and their degree of importance in the prediction process by introducing a weighting function. Indeed, the PSO algorithm is employed to learn and optimize weights of these features. The results on the Movielens 1 M dataset show that the proposed model can achieve an F-measure of 45.51% with precision as 68.64%. Furthermore, the enhancement in MAE and RMSE can respectively reach 41.63% and 39.69% compared with the state-of-the-art techniques.

scholarly journals The First National Survey of Cadmium in Cacao Farm Soil in Colombia

Agronomy ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 761
Author(s):  
Daniel Bravo ◽  
Clara Leon-Moreno ◽  
Carlos Alberto Martínez ◽  
Viviana Marcela Varón-Ramírez ◽  
Gustavo Alfonso Araujo-Carrillo ◽  
...  
Keyword(s):  
Graphical Models ◽  
Partial Correlation ◽  
National Level ◽  
Prediction Method ◽  
Correlation Coefficients ◽  
Predictive Performance ◽  
Nationwide Survey ◽  
Critical Discussion ◽  
Cadmium Content ◽  
Soil Variables

This study represents the first nationwide survey regarding the distribution of Cd content in cacao-growing soils in Colombia. The soil Cd distribution was analyzed using a cold/hotspots model. Moreover, both descriptive and predictive analytical tools were used to assess the key factors regulating the Cd concentration, considering Cd content and eight soil variables in the cacao systems. A critical discussion was performed in four main cacao-growing districts. Our results suggest that the performance of a model using all the variables will always be superior to the one using Zn alone. The analyzed variables featured an appropriate predictive performance, nonetheless, that performance has to be improved to develop a prediction method that might be used nationwide. Results from the fitted graphical models showed that the largest associations (as measured by the partial correlation coefficients) were those between Cd and Zn. Ca had the second-largest partial correlation with Cd and its predictive performance ranked second. Interestingly, it was found that there was a high variability in the factors correlated with Cd in cacao growing soils at a national level. Therefore, this study constitutes a baseline for the forthcoming studies in the country and should be reinforced with an analysis of cadmium content in cacao beans.

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