Credit Model Research Articles

Analyzing Likert scale surveys with Rasch models

Likert-scale surveys have been used in applied linguistics to make many research claims, and thus it is important to validate our score interpretations. The present study aims to demonstrate the usefulness of the Rasch partial credit model (PCM) and the Rasch rating scale model (RSM) for score interpretations of Likert-scale surveys given these models’ limited use in applied linguistics. The study used publicly available data shared by Weng (2020), where 182 students in foreign language programs at an American college responded to an eight-item, five-point Likert-scale survey intended to measure foreign language anxiety (FLA). The RSM and the PCM flagged two items that are potentially problematic due to item negation, item reversal, and double-barreled wording. The two models also suggested that the strongly disagree and strongly agree options help distinguish respondents. Content analysis also indicated that the undecided option may represent FLA only for one item, questioning the treatment of 3 as higher than 1 and 2 or as lower than 4 and 5 on an interval scale. These findings suggest that raw scores need to be interpreted cautiously, highlighting the great potential of the RSM and the PCM to facilitate our score interpretations of Likert-scale surveys.

Development of business architecture of the banking sector based on public-private partnership

The purpose of the paper is to identify promising areas of business architecture of the banking sector of Ukraine’s economy based on public-private partnerships. Business architecture integrates risks due to the predominance in a certain period of development of the banking sector of different business models. Its development should involve the subordination of private interests of the banking business to national and public needs to achieve economic growth. Such a public-private partnership should become an institutional tool for the formation and functioning of a business architecture, based on socially responsible banking.Development directions of business architecture of the Ukrainian banking sector based on public-private partnership are determined by the results of correlation and regression assessment of the impact of business architecture on economic growth in 2015–2020.The generalization of the effects on gross investment and gross consumption allows identifying the following areas for targeted changes in business architecture of the banking sector in Ukraine’s economy: 1) reducing the lending activity of banks with retail, corporate, and universal business models; 2) incitement the lending activity of banks with a corporate business model with retail financing and a business model of limited credit intermediation.The paper substantiates the feasibility of transition to mesoprudential banking regulation and supervision. The main priority of this approach is to reduce systemic risks, which is determined by the propensity for similar risks within groups of financial institutions with the same business models.

A core–periphery framework for understanding the place of Latin America in the global architecture of finance

Abstract This paper contributes to the understanding of subordinate financialisation in emerging and developing economies by setting out a novel core–periphery framework that elucidates the place of Latin America in the global architecture of finance. This framework builds on the centre–periphery financial model of uneven regional credit and economic growth, originally proposed by Victoria Chick and Sheila Dow in 1988. In the era of deregulated financial flows and market-based credit, the core–periphery relationship has become a three-level hierarchical system, in which Latin American nations occupy a subordinate place. The key drivers of this structural shift within these nations have been the liberalisation of cross-border financial flows and investment, the deregulation of banking and the adoption of private pension systems. These drivers’ adoption can be traced to both push and pull factors: specifically, recurrent financial crises requiring external intervention (especially by the International Monetary Fund (IMF)), and the possibility of engaging with the financial instruments and megabanks driving the globalisation of finance. Participating in this hierarchical system has required importing elements of the financial architecture that evolved in the 1980s in advanced economies and has also arguably deepened this region’s financial dependency and vulnerability.

Measuring Satisfaction With Upper Limb Prostheses: Orthotics and Prosthetics User Survey Revision That Includes Issues of Concern to Women

ObjectiveTo (1) modify the Orthotics and Prosthetics User Survey (OPUS) Client Satisfaction with Device (CSD) instrument to incorporate issues of concern to women and (2) evaluate measure's structural and concurrent validity and reliability in persons with upper limb amputation (ULA). DesignCross-sectional survey study with retest after 2 weeks. Exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and Rasch analyses were used to select items and examine differential item functioning, range of coverage, and person and item reliability. Test-retest reliability was evaluated with intraclass correlation coefficients. Pearson correlations were used to estimate associations with other prosthesis satisfaction measures. SettingTelephone administered survey. ParticipantsConvenience sample of 468 participants in the US (N=468; 19.9% women) with ULA, including a 50-person retest subsample (4% female). InterventionsNot applicable. Main Outcome MeasuresModified OPUS CSD. ResultsEFA suggested 3 subscales: Comfort, Appearance, and Utility. CFA found acceptable model fit. After dropping items with poor fit and high pairwise correlations in Rasch partial credit models, CFA model fit indices were acceptable (comparative fit index=0.959, Tucker-Lewis Index=0.954, root mean square error of approximation=0.082). Rasch person reliability was 0.62 (Utility), 0.77 (Appearance), and 0.82 (Comfort). Cronbach α was 0.81, 87, and 0.71 for Comfort and Appearance, and Utility subscales, respectively. Correlations between the modified CSD, the original CSD, and the Trinity Amputation and Prosthesis Experience Satisfaction Scale were 0.54-0.94. ConclusionsWe identified 3 subscales: Comfort (6 items), Appearance (8 items), and Utility (4 items) with 7 new items identified as important to women. The subscales demonstrate evidence of sound concurrent structural and test-retest reliability and concurrent validity. The Appearance and Comfort subscales have good reliability for group-level use in clinical and research applications, whereas the Utility subscale had poor to fair person reliability but excellent item reliability.

Healthcare service utilization patterns and patient experience in persons with spinal cord injury: a comparison across 22 countries

BackgroundPersons with spinal cord injury frequently visit numerous clinical settings. Such all-around experience of the system may serve as a comprehensive experience indicator. This study compared the patient experience of persons with chronic SCI in relation to healthcare service utilization patterns in 22 countries, hypothesizing that primary-care oriented patterns would offer a better experience.MethodsThis study was based on International Spinal Cord Injury Survey with 12,588 participants across 22 countries worldwide. Utilization patterns/clusters were identified by cluster analysis and experience score – by the partial credit model. The association between healthcare utilization and experience at the provider and cluster level was explored by regression analysis.ResultsThe highest share of visits was to primary care physicians (18%) and rehabilitation physicians (16%). Utilization patterns had diverse orientations: from primary care to specialized and from inpatient to outpatient. The experience was reported as very good and good across different dimensions: 84% reported respectful treatment; 81% – clear explanations; 77% – involvement in decision making; 65% – satisfaction with care. The average experience score (0–100) was 64, highest – 74 (Brazil) and the lowest – 52 (Japan, South Korea). Service utilization at provider and at cluster levels were associated with patient experience, but no utilization pattern resulted in uniformly better patient experience.ConclusionWhile there are distinct patterns between countries on how persons with chronic SCI navigate the healthcare system, we found that different utilization patterns led to similar patient experience. The observed difference in patient experience is likely determined by other contextual factors than service utilization.

Типологія чинників формування моделей кредитно-інвестиційної політики в національній економіці

The article considers the approaches to defining the concept of «credit and investment policy» and the factors influencing the formation of models of credit and investment policy in the national economy. The authors typologize all factors of influence in five groups: institutional, economic, sociopsychological, infrastructural and technological. The authors propose to include the following factors to the technological group: the share of non-cash transactions, the number of broadband Internet users and the level of use of information and communication technologies. It is also suggested to add to the existing factors the following: level of financial literacy and technical education of the population, existence of state and regional investment funds, open accreditation of investment advisers, penalties for violation of investment or lending conditions, regulation of investment funds and credit unions, public confidence in state bodies, the presence of active business angels, access to credit resources, investor protection, venture capital, the amount of savings in the population. It is worth noting that the level of financial literacy has a significant impact due to the fact that the population with a higher level of financial literacy will invest more in their own savings, which will lead to an increase in private investment in Ukraine. Developed countries have long introduced educational financial and investment programs to improve financial knowledge, thereby encouraging people to save more and, as a result, to invest. Another important aspect is the development of financial literacy in the younger generation, because, according to the Organization for Economic Cooperation and Development, the purchasing power of young people (up to 25 years) is growing every year. It is concluded that the process of developing models of credit and investment policy and methods of evaluating their effectiveness need further research. Particular attention should be paid to the development of practical tools and methods for developing the credit and investment potential of the state.

Uirt: A command for unidimensional IRT modeling

In this article, I introduce the uirt command, which allows one to estimate parameters of a variety of unidimensional item response theory models (two-parameter logistic model, three-parameter logistic model, graded response model, partial credit model, and generalized partial credit model). uirt has extended item-fit analysis capabilities, features multigroup modeling, allows testing for differential item functioning, and provides tools for generating plausible values with a latent regression conditioning model. I provide examples to illustrate cases where uirt can be especially useful in conducting analyses within the item response theory approach.

Public attitudes toward different management scenarios for “surplus” dairy calves

As awareness grows, some traditional management practices used by the dairy industry will be questioned by members of the public. Therefore, to maintain its social license to operate, the industry needs to account for public perspectives when developing future directions. Our aims were to assess attitudes of members of the public toward the management of surplus calves not needed for milk production on dairy farms, and to assess how specific calf management practices might influence these attitudes. A mixed-methods questionnaire was developed and distributed online in the United States and in Canada. After reading an introductory paragraph stating that surplus calves are generally used for meat production, participants were randomly allocated into groups and read 1 of 4 scenarios that described different surplus calf management practices in more detail. The scenarios followed a 2 × 2 factorial design, and the factors that differed were the calf's age at slaughter (≤2 wk vs. ≥12 mo), and whether the calf was separated from the cow at birth or sometime later. Data representative of key census demographics from 998 participants were analyzed. Quantitative data analysis included descriptive statistics, nonparametric tests, generalized partial credit models, and linear regression models. For qualitative data, we used reliability thematic analysis. Overall, participants were slightly positive in their attitudes toward the introductory paragraph, and participants in the groups in which the calf was slaughtered after 12 mo of age often specifically linked their acceptance of the practice to the fact that the calves' lives had a purpose (i.e., contributing meaningfully to the beef supply). In contrast, only 3% of the participants regarded a slaughter age of <1 mo as appropriate. Participants in the groups in which calves were slaughtered within 2 wk after birth had more negative attitudes, and these attitudes declined even further when the calf was separated from the cow soon after birth. Besides the 2 main factors (age at slaughter and cow-calf separation), information on pasture access, the healthiness of the meat from the calves, and the exact age of slaughter were also considered important by participants to make a more informed decision about their view on surplus calf management. Overall, our results indicate that failure by the dairy industry to provide assurances that excess dairy calves have a reasonable length of life and that this life has purpose (i.e., contributes to the beef supply chain) places the industry at odds with public values. Also, as awareness grows, the practice of early cow-calf separation will be increasingly questioned by the public; failure to begin discussions on this topic will increase the risk that future decisions about this topic will be made in the absence of the farmer.

Development of an integrated ability assessment instrument in reaction rate material

This research aimed to develop a valid and reliable integrated ability assessment instrument (IAAI) to measure the multiple representations and chemical literacy of senior high school students related to the reaction rates. The framework developed in this research was implemented based on a 4-D model (defining, designing, developing, and disseminating). The integrated assessment consisted of five items of essay questions. The preliminary version of the IAAI was initially piloted on reviews by experts, and the paper-pencil test was given to a group of students. The obtained data were analyzed using Item Response Theory (IRT). In addition, Generalized Partial Credit Model (GPCM) model was conducted to examine the parameter quality, which estimated the test items. The content validity, construct validity, and quality of the items suggest that the integrated assessment ability instrument has a high score in validity and reliability. The analysis results of the instrument trial data indicate that the integrated abilities of students are in the medium category.

Internal structure and classification of pelvic floor dysfunction distress by PFDI-20 total score

PurposeTo evaluate the internal structure (structural validity and internal consistency) and propose a classification for the distress caused by the presence of pelvic floor dysfunction (PFD) symptoms based on the total score of the Pelvic Floor Distress Inventory (PFDI-20).MethodsCross-sectional study conducted with Brazilian women over 18 years of age. Exploratory and confirmatory factor analysis were performed with Parallel Analysis and to test three models to compare them with the Root Mean Square Error of Approximation (RMSEA) and Comparative Fit Index (CFI). Internal consistency was calculated using Cronbach's alpha. Partial credit model (PCM) was performed to classify the total score of the PFDI-20.ResultsData from 237 women (49.62 ± 16.95 years) were analyzed. The one-dimensional structure had 43.74% of the explained variance with α = 0.929. The one-dimensional model was the most appropriate (CFI = 0.987 and RMSEA = 0.022). The total PFDI-20 score was classified as the absence of symptoms (score zero), symptoms with mild distress (1 to 15 points), symptoms with moderate distress (16 to 34 points), and symptoms with severe distress (35 to 40 points).ConclusionThe PFDI-20 has an one-dimensional structure and the distress caused by the presence of PFD symptoms can be classified as mild, moderate and severe. Health professionals and future studies can use our classification to facilitate the understanding of the patient's health status and to obtain other analyses on the severity of the distress of the symptoms of PFD.

Evidence for validity of the Swedish self-rated 36-item version of the World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) in patients with mental disorders: a multi-centre cross-sectional study using Rasch analysis

BackgroundThe World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) is a generic instrument for the assessment of functioning in six domains, resulting in a total health-related disability score. The aim of this study was to investigate the psychometric properties of the Swedish-language version of the self-rated 36-item version in psychiatric outpatients with various common psychiatric diagnoses using Rasch analysis. A secondary aim was to explore the correlation between two methods of calculating overall scores to guide clinical practice: the WHODAS simple (summative) model and the WHODAS complex (weighted) model.MethodsCross-sectional data from 780 Swedish patients with various mental disorders were evaluated by Rasch analysis according to the partial credit model. Bivariate Pearson correlations between the two methods of calculating overall scores were explored.ResultsOf the 36 items, 97% (35 items) were within the recommended range of infit mean square; only item D4.5 (Sexual activities) indicated misfit (infit mean square 1.54 logits). Rating scale analysis showed a short distance between severity levels and disordered thresholds. The two methods of calculating overall scores were highly correlated (0.89–0.99).ConclusionsThe self-administered WHODAS 2.0 fulfilled several aspects of validity according to Rasch analysis and has the potential to be a useful tool for the assessment of functioning in psychiatric outpatients. The internal structure of the instrument was satisfactorily valid and reliable at the level of the total score but demonstrated problems at the domain level. We suggest rephrasing the item Sexual activities and revising the rating scale categories. The WHODAS simple model is easier to use in clinical practice and our results indicate that it can differentiate function among patients with moderate psychiatric disability, whereas Rasch scaled scores are psychometrically more precise even at low disability levels. Further investigations of different scoring models are warranted.

Finalization and Validation of Questionnaire and Algorithm of SPUR, a New Adherence Profiling Tool.

PurposeThe SPUR (Social, Psychological, Usage and Rational) Adherence Profiling Tool is a recently developed adaptive instrument for assessing key patient-level drivers for non-adherence. This study describes the SPUR questionnaire’s finalization and psychometric evaluation.Patients and MethodsData were collected through an online survey among patients with type 2 diabetes included by general practitioners and diabetologists in France. The survey included four questionnaires, SPUR and three validated adherence measures: BMQ, MARS and ACCEPT. Item-level analysis and a partial credit model (PCM) were performed to refine the response option coding of SPUR items. The final item selection of SPUR was defined using a PCM and a principal component analysis (PCA). Construct validity, concurrent validity and known-groups validity were assessed on the final SPUR questionnaire.ResultsA total of 245 patients (55% men, mean age of 63 years) completed the survey remotely and were included in this analysis. Refining response option coding allowed a better discrimination of patients on the latent trait. After item selection, a short, an intermediate, and a long form composed the final SPUR questionnaire. The short form will be used to screen patients for risk and then the other forms will allow the collection of further information to refine the risk assessment and decide the best levers for action. Results obtained were supportive of the construct validity of the forms. Their concurrent validity was demonstrated: moderate to high significant correlations were obtained with BMQ, MARS and ACCEPT scores. Their known-groups validity were shown with a logical pattern of higher scores obtained for patients considered non-adherent and significant differences between the scores obtained for patients considered adherent versus non-adherent.ConclusionSPUR is a valid tool to evaluate the risk of non-adherence of patients, allowing effective intervention by providing insights into the respective individual reasons for lack of adherence.

An uncertainty-oriented cost-sensitive credit scoring framework with multi-objective feature selection

• An uncertainty-oriented credit scoring framework with multi-objective feature selection is developed to tackle the credit classification task under uncertainty. • This study extends the use of cost space to feature selection in the credit scoring process. • The proposed credit scoring framework can provide a series of Pareto-optimal credit scoring models to fit different decision-making contexts. • The cost plot enables credit decision-makers to see the results of different credit scoring models with different risk sources and corresponding expected costs. In order to solve the problem of uncertain misclassification costs and class distributions in credit scoring tasks, an uncertainty-oriented credit scoring framework based on a multi-objective feature selection strategy is proposed in this study. This proposed framework searches for a pool of Pareto-optimal credit scoring models with different feature subsets without the assumption of the operating condition (misclassification costs and class distributions) information. Specifically, the searching process concerns the trade-off of the False Positive Rate and the False Negative Rate using a binary multi-objective particle swarm optimization (BMOPSO) algorithm. By visualizing the Pareto-optimal solutions in cost space, credit decision-makers can select an optimal compromise model based on their decision-making contexts. The proposed framework is compared with baseline models on three retail credit scoring datasets. The experimental results show that the proposed framework could find out the optimal credit model with minimal misclassification cost for almost all possible operating conditions.

Evaluation of the Norwegian version of the Dyspnoea-12 questionnaire in patients with COPD

BackgroundThe Dyspnoea-12 (D-12) questionnaire is widely used and tested in patients with breathing difficulties. The objective of this study was to translate and undertake the first evaluation of the measurement...

Fraud detection under the unbalanced class based on gradient boosting

Credit fraud modeling is an important topic covered by researchers. Overdue risk management is a critical business link in providing credit loan services. It directly impacts the rate of return and the bad debt percentage of lending organizations in this sector. Credit financial services have benefited the general public as a result of the development of the mobile Internet, and overdue risk control has evolved from the manual judgment that relied on rules in the past to a credit model built using a large amount of customer data to predict the likelihood of customers becoming delinquent. When creating a credit rating model, the emerging nature of the credit samples makes the minority class sample score very few; that is, when a large number of actual samples are obtained, this causes machine learning models to be biased towards the majority class when training. Traditional data balancing methods can reduce the bias of models to the majority category when the data is relatively unbalanced rather than excessive. Gradient boosting algorithms (XGBoost and CatBoost) are proposed in this paper to model highly unbalanced data to detect credit fraud. To find hyperparameters and determine the accuracy of the minority class as an optimization function of the model, Bayesian optimization is used to increase the model's accuracy for the minority class. The paper was tested with real European credit card fraud data. The results were compared to traditional machine learning (decision trees and logistic regression) and the performance of the bagging algorithm (random forest). For comparison, the traditional data balancing method (Oversample) is used

LITERATURE REVIEW OF AGRIBUSINESS PRODUCT FINANCING DEVELOPMENT MODEL AT SHARIA BANK

This study aims to analyze the development model of agribusiness product financing in Islamic banks in Indonesia. The data used in the analysis related to the research topic were taken from journal articles on Google Scholar. Data from these sources were then analyzed using a literature review approach. Based on the results of the analysis, it was found that several models of agribusiness product development at Islamic banks in Indonesia are different from the credit model, this Islamic financing is interest free, profit sharing is based on profit sharing made after the transaction period ends. This paper aims to introduce the Islamic financing model and the prospects for its implementation in the agricultural sector. The results of the study show that Islamic financing is prospective enough to strengthen capital in the agricultural sector. To support its implementation in the agricultural sector, it is necessary to take sides with policy makers as well as intensive socialization of the principles of Islamic financing. The modeling used in this research is a literature study or literature review. The literature study in this research was conducted to study the definition of keywords, to deepen theories and concepts and to identify variables related to the background and context of the research. Study of literature related to the model of developing financing for agribusiness products at Islamic banks in Indonesia, searching for journals using Google Scholar with the keywords "Agribusiness Products" and "Islamic Banks". ” found as many as 1040 papers but after reviewing there were 8 appropriate journal papers related to the title "Development of Agribusiness Products in Islamic Banks" with category years (2008-2021).

Default or profit scoring credit systems? Evidence from European and US peer-to-peer lending markets

For the emerging peer-to-peer (P2P) lending markets to survive, they need to employ credit-risk management practices such that an investor base is profitable in the long run. Traditionally, credit-risk management relies on credit scoring that predicts loans’ probability of default. In this paper, we use a profit scoring approach that is based on modeling the annualized adjusted internal rate of returns of loans. To validate our profit scoring models with traditional credit scoring models, we use data from a European P2P lending market, Bondora, and also a random sample of loans from the Lending Club P2P lending market. We compare the out-of-sample accuracy and profitability of the credit and profit scoring models within several classes of statistical and machine learning models including the following: logistic and linear regression, lasso, ridge, elastic net, random forest, and neural networks. We found that our approach outperforms standard credit scoring models for Lending Club and Bondora loans. More specifically, as opposed to credit scoring models, returns across all loans are 24.0% (Bondora) and 15.5% (Lending Club) higher, whereas accuracy is 6.7% (Bondora) and 3.1% (Lending Club) higher for the proposed profit scoring models. Moreover, our results are not driven by manual selection as profit scoring models suggest investing in more loans. Finally, even if we consider data sampling bias, we found that the set of superior models consists almost exclusively of profit scoring models. Thus, our results contribute to the literature by suggesting a paradigm shift in modeling credit-risk in the P2P market to prefer profit as opposed to credit-risk scoring models.

Rasch Validation of the Mini-BESTest in People With Parkinson Disease.

The Mini-BESTest is a balance measure with robust psychometric properties widely used in people with Parkinson disease. The aim of this study was to examine-with advanced psychometric techniques-some key properties of the Mini-BESTest (including unidimensionality, functioning of rating categories, internal construct validity, reliability indexes) in a consecutive sample of individuals with Parkinson disease admitted for balance rehabilitation. Confirmatory factor analysis and Rasch analysis (partial credit model) were performed on 193 individual raw scores of the Mini-BESTest items. Confirmatory factor analysis fit indices and principal component analysis of the residuals confirmed the scale's unidimensionality. At Rasch analysis, the 3-level rating scale demonstrated appropriate functioning. All items fitted the Rasch model. Item response dependence was negligible. No differential item functioning was found across gender and age groups. We confirmed and extended the evidence (demonstrated in different populations) on the general psychometric soundness of the Mini-BESTest, even when tested with rigorous statistical methods. In addition, 2 forms were created: (i) to transform raw scores into linear estimates of dynamic balance; and (ii) to compare the individual's item responses with those expected by the Rasch model (thus providing an aid for tailored interventions) and manage missing responses. Further independent studies using advanced psychometric techniques are warranted, also in people with balance disturbances of different etiology. Our study further increases the confidence in using the Mini-BESTest to assess dynamic balance in people with Parkinson disease and provides some useful additional clinical aids for interpreting the results and calculating more precise change scores.See the Supplementary Video, available at: http://links.lww.com/JNPT/A384.

Effects of Using Double Ratings as Item Scores on IRT Proficiency Estimation

ABSTRACT This article presents the performance of item response theory (IRT) models when double ratings are used as item scores over single ratings when rater effects are present. Study 1 examined the influence of the number of ratings on the accuracy of proficiency estimation in the generalized partial credit model (GPCM). Study 2 compared the accuracy of proficiency estimation of two IRT models (GPCM versus the hierarchical rater model, HRM) for double ratings. The main findings were as follows: (a) rater effects substantially reduced the accuracy of IRT proficiency estimation; (b) double ratings relieved the negative impact of rater effects on proficiency estimation and improved the accuracy relative to single ratings; (c) IRT estimators showed different patterns in the conditional accuracy; (d) as more items and a larger number of score categories were used, the accuracy of proficiency estimation improved; and (e) the HRM consistently showed better performance than the GPCM.

Rasch Analysis of the Physical Activity Enjoyment Scale Among 9th- and 10th-Grade Students

Rasch Model analysis was used to evaluate construct validity and reliability of the Physical Activity Enjoyment Scale (PACES) in an adolescent population. A total of 349 9th and 10th graders (180 male; 169 female), aged 13 to 15 years (M = 14.13 SD = .793), completed the 18-item PACES scale at the conclusion of physical education classes. Responses to PACES items were analyzed using Rasch partial credit model. Of the 18 PACES items, five were identified as misfit items and were removed. The remaining 13 good-fit items (difficulty level ranged from -0.81 for Item #10 to 0.66 logits for Item #18) demonstrated one dimension which accounted for 62.4% of the variance, with the person separation index was 3.01; however, the 6-point Likert response format was not appropriate for some remaining items. No items presented differential item functioning (DIF) between genders. Rasch analysis supported the construct validity and reliability of PACES to assess PA enjoyment among 9th and 10th grade high school students after removing five misfit items.