scholarly journals Deflation-Corrected Estimators of Reliability

2022 ◽  
Vol 12 ◽  
Author(s):  
Jari Metsämuuronen
Keyword(s):  
Correlation Coefficient ◽  
Principal Component ◽  
Factor Loading ◽  
Difficulty Level ◽  
Polychoric Correlation ◽  
Item Score

Underestimation of reliability is discussed from the viewpoint of deflation in estimates of reliability caused by artificial systematic technical or mechanical error in the estimates of correlation (MEC). Most traditional estimators of reliability embed product–moment correlation coefficient (PMC) in the form of item–score correlation (Rit) or principal component or factor loading (λi). PMC is known to be severely affected by several sources of deflation such as the difficulty level of the item and discrepancy of the scales of the variables of interest and, hence, the estimates by Rit and λi are always deflated in the settings related to estimating reliability. As a short-cut to deflation-corrected estimators of reliability, this article suggests a procedure where Rit and λi in the estimators of reliability are replaced by alternative estimators of correlation that are less deflated. These estimators are called deflation-corrected estimators of correlation (DCER). Several families of DCERs are proposed and their behavior is studied by using polychoric correlation coefficient, Goodman–Kruskal gamma, and Somers delta as examples of MEC-corrected coefficients of correlation.

scholarly journals The Development of Athlete Performance Capabilities Index (APCI) Model for Male U12 Player Selection using Multivariate Analysis

2018 ◽  
Vol 7 (4.34) ◽  
pp. 97
Author(s):  
Mohamad Razali Abdullah ◽  
Hafizan Juahir ◽  
N. Mohamad Shukri ◽  
N. A. Fuat ◽  
N. A. Mohd Ros ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Factor Score ◽  
Principal Component ◽  
Factor Loading ◽  
Group Classification ◽  
Performance Group ◽  
Two Factors ◽  
Low Performance ◽  
High Factor Loading ◽  
Athlete Performance

This study develops an Athlete Performance Capabilities Index (APCI) model using multivariate analysis for selecting the best player of under twelve (U12).  Measurement of anthropometrics and physical fitness were evaluated among 178 male players aged 12±0.52 years. Factor score derived by Principal Component Analysis were used to obtain a model for APCI and Discriminant Analysis (DA) were conducted to validate the correctness of group classification by APCI. Result was found two factors with eigenvalues greater than 1 were extracted which accounted for 62.00% of the variations present in the original variables. The two factors were used to obtain the factor score coefficients explained by 35.72% and 26.67% of the variations in athlete performance respectively. Factor 1 revealed high factor loading on fitness compared to Factor 2 as it was significantly related to anthropometrics. A model was obtained using standardized coefficient of factor 1. Three clusters of performance were shaped in view by categorizing APCI ≥ 75%, 25% ≤ APCI < 75% and APCI < 25% as high, moderate and low performance group respectively. Three discriminated variables out of thirteen variables were obtained using Forward and Backward stepwise mode of DA, which were weight, standing broad jump, and 40 meters’ speed. Such variables were established as essential indicator for selecting the best player among male U12.   

scholarly journals Complex principal component analysis of mass balance changes on the Qinghai–Tibetan Plateau

2017 ◽  
Vol 11 (3) ◽  
pp. 1487-1499 ◽  
Author(s):  
Jingang Zhan ◽  
Hongling Shi ◽  
Yong Wang ◽  
Yixin Yao
Keyword(s):  
Tibetan Plateau ◽  
Mass Balance ◽  
Correlation Coefficient ◽  
El Niño ◽  
El Nino ◽  
Principal Component ◽  
Mass Change ◽  
Eastern Himalayas ◽  
The Third ◽  
Northwestern India

Abstract. Climatic time series for Qinghai–Tibetan Plateau locations are rare. Although glacier shrinkage is well described, the relationship between mass balance and climatic variation is less clear. We studied the effect of climate changes on mass balance by analyzing the complex principal components of mass changes during 2003–2015 using Gravity Recovery and Climate Experiment satellite data. Mass change in the eastern Himalayas, Karakoram, Pamirs, and northwestern India was most sensitive to variation in the first principal component, which explained 54 % of the change. Correlation analysis showed that the first principal component is related to the Indian monsoon and the correlation coefficient is 0.83. Mass change on the eastern Qinghai plateau, eastern Himalayas–Qiangtang Plateau–Pamirs area and northwestern India was most sensitive to variation of the second major factor, which explained 16 % of the variation. The second major component is associated with El Niño; the correlation coefficient was 0.30 and this exceeded the 95 % confidence interval of 0.17. Mass change on the western and northwestern Qinghai–Tibetan Plateau was most sensitive to the variation of its third major component, responsible for 6 % of mass balance change. The third component may be associated with climate change from the westerlies and La Niña. The third component and El Niño have similar signals of 6.5 year periods and opposite phases. We conclude that El Niño now has the second largest effect on mass balance change of this region, which differs from the traditional view that the westerlies are the second largest factor.

scholarly journals Psychometric Properties of the Moore Index of Nutrition Self-Care in Arabic: A Study among Saudi Adolescents at King Saud University, Riyadh, Saudi Arabia

2020 ◽  
Vol 2020 ◽  
pp. 1-7 ◽  
Author(s):  
Adel Bashatah ◽  
Khalid A. Alahmary
Keyword(s):  
Saudi Arabia ◽  
Self Care ◽  
Principal Component ◽  
Factor Loading ◽  
Arabic Language ◽  
Validity And Reliability ◽  
Cronbach’S Alpha ◽  
King Saud University ◽  
Adolescent Students ◽  
Cronbach's Alpha

Background and Objective. The Moore Index of Nutrition Self-Care (MIN-SC) questionnaire has been used widely in both English and Spanish languages. The purpose of this study is to convert MIN-SC into the Arabic language and to test the translated tool for validity and reliability among adolescents in Saudi Arabia. Method. The psychometric characteristics of MIN-SC were assessed using college freshman students at King Saud University in Riyadh, Saudi Arabia. The validity and reliability were examined using Cronbach’s alpha coefficient. The construct validity was examined through principal component analysis. Results. The MIN-SC instrument was shown to be internally consistent with reliable scoring (Cronbach’s alpha = 0.910). Exploratory factor analysis resulted in 42 items loading on three main components: estimative, production, and transitional, with a factor loading of eigenvalues >2. The final model explained 38% of the variance. Conclusion. The Arabic version of MIN-SC was shown to be a valid and reliable tool for assessing attitude toward nutrition among adolescent students.

scholarly journals Classifying Parkinson’s Disease Based on Acoustic Measures Using Artificial Neural Networks

Sensors ◽  
2018 ◽  
Vol 19 (1) ◽  
pp. 16 ◽  
Author(s):  
Lucijano Berus ◽  
Simon Klancnik ◽  
Miran Brezocnik ◽  
Mirko Ficko
Keyword(s):  
Neural Networks ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Feature Selection ◽  
Artificial Neural Networks ◽  
Correlation Coefficient ◽  
Principal Component ◽  
Test Accuracy ◽  
Artificial Neural ◽  
Prediction Problems

In recent years, neural networks have become very popular in all kinds of prediction problems. In this paper, multiple feed-forward artificial neural networks (ANNs) with various configurations are used in the prediction of Parkinson’s disease (PD) of tested individuals, based on extracted features from 26 different voice samples per individual. Results are validated via the leave-one-subject-out (LOSO) scheme. Few feature selection procedures based on Pearson’s correlation coefficient, Kendall’s correlation coefficient, principal component analysis, and self-organizing maps, have been used for boosting the performance of algorithms and for data reduction. The best test accuracy result has been achieved with Kendall’s correlation coefficient-based feature selection, and the most relevant voice samples are recognized. Multiple ANNs have proven to be the best classification technique for diagnosis of PD without usage of the feature selection procedure (on raw data). Finally, a neural network is fine-tuned, and a test accuracy of 86.47% was achieved.

scholarly journals Team-Based Learning Student Assessment Instrument (TBL-SAI) for measuring the effectiveness of TBL in a Saudi Medical School: Psychometric Analysis and differences by academic years

2019 ◽  
Author(s):  
Mutasim E Ibrahim
Keyword(s):  
Medical Students ◽  
Medical School ◽  
Student Assessment ◽  
Reliability And Validity ◽  
Principal Component ◽  
Factor Loading ◽  
Assessment Instrument ◽  
Cronbach’S Alpha ◽  
Cronbach's Alpha ◽  
Team Based Learning

Abstract Background Increasing the use of Team Based Learning (TBL) in health profession education reinforce the need to develop a proper instrument for measuring the applicability of this method. This study aimed to examine the psychometric properties of TBL-SAI and the mean score of instrument subscales by the different academic year of the students. Methods Across-sectional study was conducted at the University of Bisha, College of Medicine (UBCOM), Saudi Arabia. Medical students from second to fourth were included in the study. Participants were completed the TBL-SAI items to measure three subscales of accountability, preference for a lecture or TBL and satisfaction. Cronbach’s alpha, factor analysis, were checked the reliability and validity of the instrument. A principal component analysis (PCA) with varimax rotation was conducted on each subscale. ANOVA analyzed the TBL effectiveness related to the different years of medical school. Results Cronbach’s alpha was 0.798 and factor loading was greater than 0.40 for all the items, indicating the reliability and validity of the scale. In a PCA, accountability items generated two factors with loading >0.40, except items one and four. All preference and satisfaction items have factors loading > 0.40. Fourth-year students’ obtained significant highest mean scores for accountability (p=0.0.49), preferences (p=0.001) and satisfaction (p<0.001) compared to third and second years students. Conclusions TBL-SAI is a sound tool to measure the favor of TBL among medical students. Longitudinal studies are recommended to bring a clear picture of the effectiveness of TBL in UBCOM.

scholarly journals Bivariate Distributions Underlying Responses to Ordinal Variables

Psych ◽  
2021 ◽  
Vol 3 (4) ◽  
pp. 562-578
Author(s):  
Laura Kolbe ◽  
Frans Oort ◽  
Suzanne Jak
Keyword(s):  
Correlation Coefficient ◽  
Latent Variables ◽  
Ordinal Data ◽  
Bivariate Normal Distribution ◽  
Polychoric Correlation ◽  
Bivariate Distributions ◽  
Normal Distributions ◽  
Ordinal Variables ◽  
Bivariate Normal ◽  
Bivariate Normality

The association between two ordinal variables can be expressed with a polychoric correlation coefficient. This coefficient is conventionally based on the assumption that responses to ordinal variables are generated by two underlying continuous latent variables with a bivariate normal distribution. When the underlying bivariate normality assumption is violated, the estimated polychoric correlation coefficient may be biased. In such a case, we may consider other distributions. In this paper, we aimed to provide an illustration of fitting various bivariate distributions to empirical ordinal data and examining how estimates of the polychoric correlation may vary under different distributional assumptions. Results suggested that the bivariate normal and skew-normal distributions rarely hold in the empirical datasets. In contrast, mixtures of bivariate normal distributions were often not rejected.

scholarly journals Toward a model of relationship between the overall and the destination attributes satisfaction

2020 ◽  
Vol 25 (2) ◽  
pp. 67-81
Author(s):  
Ljiljana Najev Čačija ◽  
Davorka Mikulić ◽  
Daša Dragnić
Keyword(s):  
Conceptual Model ◽  
Principal Component ◽  
Final Analysis ◽  
Factor Loading ◽  
Measurement Scales ◽  
Pull Factors ◽  
Tourist Satisfaction ◽  
Rotation Method ◽  
The Impact ◽  
The Town

This study presents a preliminary research towards a conceptual model of relationship between the overall and the destination attributes satisfaction. Precisely, the paper explores and classifies destination pull factors as a precondition to design a conceptual model. Therefore, the first step was to categorise destination attributes into meaningful groups of pull factors that provide greater efficiency in achieving and maintaining a desired perception of destination quality, measured by tourists’ satisfaction. The exploratory factor analysis was conducted on the sample of 289 tourists visiting the town of Split (Croatia). The required prior statistical preconditions were successfully met and the principal component analysis was conducted on 20 items with Varimax rotation method. Based on the results, four pull factors were retained in the final analysis, explaining 54.760% of the variance. In the final categorisation, factor loading was above 0.4 for all four extracted factors, with reliability of measurement scales. Major findings of this study confirm that destination attributes can be grouped in a meaningful way regarding tourist satisfaction and indicate that the extracted pull factors, representing both common and unique destination attributes, have the potential to be generally applicable. The extracted factors are the primary or fundamental offer components; additional/expanded offer components; tertiary or tendency/affinity/preference offer components and specific offer components. Recommendations for further research are given, in order to explore to what extent the tourists’ overall satisfaction is related to their satisfaction with destination attributes, and to expand the model with the impact of other moderating elements.

scholarly journals Students’ Motivation and Attitude towards the Learning of Arabic Language: A Case Study of Arabic Students in Nigerian Universities

2015 ◽  
Vol 3 (1) ◽  
pp. 51-69
Author(s):  
Arifin Mamat ◽  
Kazeem Oluwatoyin Ajape
Keyword(s):  
Second Language ◽  
Second Language Acquisition ◽  
Language Learners ◽  
Principal Component ◽  
Factor Loading ◽  
Arabic Language ◽  
Moderate Correlation ◽  
Learning Situation ◽  
Attitude And Motivation

The study of students’ motivation and attitude in second language (L2) has recently become an important concept across disciplines of second language acquisition (SLA) and communication. This study sought to validate Gadner’s (2009) Attitude Motivation Test Battery (AMBT) on a population of Arabic language learners in Nigeria, and to determine their attitudes and motivations for learning Arabic language. The sample comprised two hundred and eighty eight (288) Arabic language students from six (6) universities in Nigeria. Principal Component Analysis (PCA) was conducted to explore the dimensions of the AMBT in Nigerian context. Twenty three out of the fifty items with factor loading greater than .40 loaded on four factors with eigenvalues greater than 1.0. Four constructs of the questionnaire are: Integrativeness, Attitudes toward the learning situation, Motivation and Instrumentality. The results showed that students had high levels of both integrativeness and attitude towards the learning situation, while their levels of motivation and instrumentality was very low. There was a positive and moderate correlation  between integrativenness and attitude toward the learning situation while the correlations between attitude and motivation and integrativeness and motivation were very low. Instrumentality failed to correlate with any of the factors. Multiple regression analysis showed that attitude toward the learning situation was a good predictor of students’ integrativeness. Based on these findings, some pedagogical recommendations were provided for the improvement of the students’ motivation and attitude towards the learning of Arabic language in Nigerian universities.      

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