Showing papers on "Reliability (statistics) published in 2015"
TL;DR: The use of reliability and validity are common in quantitative research and now it is reconsidered in the qualitative research paradigm as discussed by the authors, which can also illuminate some ways to test or maximize the validity and reliability of a qualitative study.
Abstract: The use of reliability and validity are common in quantitative research and now it is reconsidered in the qualitative research paradigm. Since reliability and validity are rooted in positivist perspective then they should be redefined for their use in a naturalistic approach. Like reliability and validity as used in quantitative research are providing springboard to examine what these two terms mean in the qualitative research paradigm, triangulation as used in quantitative research to test the reliability and validity can also illuminate some ways to test or maximize the validity and reliability of a qualitative study. Therefore, reliability, validity and triangulation, if they are relevant research concepts, particularly from a qualitative point of view, have to be redefined in order to reflect the multiple ways of establishing truth. Key words: Reliability, Validity, Triangulation, Construct, Qualitative, and Quantitative This article discusses the use of reliability and validity in the qualitative research paradigm. First, the meanings of quantitative and qualitative research are discussed. Secondly, reliability and validity as used in quantitative research are discussed as a way of providing a springboard to examining what these two terms mean and how they can be tested in the qualitative research paradigm. This paper concludes by drawing upon the use of triangulation in the two paradigms (quantitative and qualitative) to show how the changes have influenced our understanding of reliability, validity and triangulation in qualitative studies.
6,438 citations
TL;DR: In this article, a new method, called best-worst method (BWM) is proposed to solve multi-criteria decision-making (MCDM) problems, in which a number of alternatives are evaluated with respect to different criteria in order to select the best alternative(s).
Abstract: In this paper, a new method, called best-worst method (BWM) is proposed to solve multi-criteria decision-making (MCDM) problems. In an MCDM problem, a number of alternatives are evaluated with respect to a number of criteria in order to select the best alternative(s). According to BWM, the best (e.g. most desirable, most important) and the worst (e.g. least desirable, least important) criteria are identified first by the decision-maker. Pairwise comparisons are then conducted between each of these two criteria (best and worst) and the other criteria. A maximin problem is then formulated and solved to determine the weights of different criteria. The weights of the alternatives with respect to different criteria are obtained using the same process. The final scores of the alternatives are derived by aggregating the weights from different sets of criteria and alternatives, based on which the best alternative is selected. A consistency ratio is proposed for the BWM to check the reliability of the comparisons. To illustrate the proposed method and evaluate its performance, we used some numerical examples and a real-word decision-making problem (mobile phone selection). For the purpose of comparison, we chose AHP (analytic hierarchy process), which is also a pairwise comparison-based method. Statistical results show that BWM performs significantly better than AHP with respect to the consistency ratio, and the other evaluation criteria: minimum violation, total deviation, and conformity. The salient features of the proposed method, compared to the existing MCDM methods, are: (1) it requires less comparison data; (2) it leads to more consistent comparisons, which means that it produces more reliable results.
2,214 citations
TL;DR: Rigour, or the integrity in which a study is conducted, is outlined and concepts such as reliability, validity and generalisability typically associated with quantitative research and alternative terminology will be compared in relation to their application to qualitative research.
Abstract: Evaluating the quality of research is essential if findings are to be utilised in practice and incorporated into care delivery. In a previous article we explored ‘bias’ across research designs and outlined strategies to minimise bias.1 The aim of this article is to further outline rigour, or the integrity in which a study is conducted, and ensure the credibility of findings in relation to qualitative research. Concepts such as reliability, validity and generalisability typically associated with quantitative research and alternative terminology will be compared in relation to their application to qualitative research. In addition, some of the strategies adopted by qualitative researchers to enhance the credibility of their research are outlined.
Assessing the reliability of study findings requires researchers and health professionals to make judgements about the ‘soundness’ of the research in relation to …
1,401 citations
TL;DR: A review article which comprehensively explores and describes the validity and reliability of a research instrument (with special reference to questionnaire) and various methods of analysing these tests with scientific principles guiding such analysis are explained.
Abstract: The importance of measuring the accuracy and consistency of research instruments (especially questionnaires) known as validity and reliability, respectively, have been documented in several studies, but their measure is not commonly carried out among health and social science researchers in developing countries. This has been linked to the dearth of knowledge of these tests. This is a review article which comprehensively explores and describes the validity and reliability of a research instrument (with special reference to questionnaire). It further discusses various forms of validity and reliability tests with concise examples and finally explains various methods of analysing these tests with scientific principles guiding such analysis.
700 citations
TL;DR: Investigation of if and how external factors could influence a largely used reliability estimator - Cronbach Alpha shows that important differences in the values of CronbachAlpha are possible due to indirect influence from external factors.
Abstract: In social economic researches we often need to measure non-observable, latent variables. For this we use special research instruments, with uni and multi dimensional scales designed for measuring the constructs of interest. Validity and reliability of these scales are crucial and special tests have been developed in this respect. Reliability concerns often arise, due to external factors that can influence the power and significance of such tests. Even for standardized instruments variations are possible, and they could seriously affect research results. The purpose of the present study is to investigate if and how external factors could influence a largely used reliability estimator - Cronbach Alpha. Several scales commonly used in marketing researches were tested, using a bootstrapping technique. Results show that important differences in the values of Cronbach Alpha are possible due to indirect influence from external factors - respondents’ age, gender, level of study, religiousness, rural/urban living, survey type and relevance of the research subject for the participants to the survey.
601 citations
TL;DR: In this article, the authors proposed a confidence interval that does not require equal variances or equal covariances and demonstrated that the proposed method performed better than alternative methods, and also presented some sample size formulas that approximate the sample size requirements for desired power or desired confidence interval precision.
Abstract: Summary
Cronbach's alpha is one of the most widely used measures of reliability in the social and organizational sciences. Current practice is to report the sample value of Cronbach's alpha reliability, but a confidence interval for the population reliability value also should be reported. The traditional confidence interval for the population value of Cronbach's alpha makes an unnecessarily restrictive assumption that the multiple measurements have equal variances and equal covariances. We propose a confidence interval that does not require equal variances or equal covariances. The results of a simulation study demonstrated that the proposed method performed better than alternative methods. We also present some sample size formulas that approximate the sample size requirements for desired power or desired confidence interval precision. R functions are provided that can be used to implement the proposed confidence interval and sample size methods. Copyright © 2014 John Wiley & Sons, Ltd.
578 citations
TL;DR: A reliability generalization meta-analysis on the Yale–Brown Obsessive Compulsive Scale is conducted to estimate the average reliability, examine the variability among the reliability estimates, search for moderators, and propose a predictive model that researchers and clinicians can use to estimates the expected reliability of the Y-BOCS.
Abstract: The Yale-Brown Obsessive Compulsive Scale (Y-BOCS) is the most frequently applied test to assess obsessive compulsive symptoms. We conducted a reliability generalization meta-analysis on the Y-BOCS to estimate the average reliability, examine the variability among the reliability estimates, search for moderators, and propose a predictive model that researchers and clinicians can use to estimate the expected reliability of the Y-BOCS. We included studies where the Y-BOCS was applied to a sample of adults and reliability estimate was reported. Out of the 11,490 references located, 144 studies met the selection criteria. For the total scale, the mean reliability was 0.866 for coefficients alpha, 0.848 for test-retest correlations, and 0.922 for intraclass correlations. The moderator analyses led to a predictive model where the standard deviation of the total test and the target population (clinical vs. nonclinical) explained 38.6% of the total variability among coefficients alpha. Finally, clinical implications of the results are discussed.
472 citations
Journal Article•
TL;DR: The use of qualitative research as scientific and complementary method of quantitative research is argued and the combination of both methods seems to be the most acceptable option and reduce the possibility of bias.
Abstract: Introduction: The research landscape was enriched with new forms of inquiry that deviated from the positivist and neopositivist paradigms. For these idealists and subjective currents, I just think science can explain reality. Objective: To argue the use of qualitative research as scientific and complementary method of quantitative research. Methods: A review of texts in which qualitative research and its possible applications in health is defined was performed. Results: The study provides quantitative information derived from the relationships between variables, however, multivariate methods applied are insufficient to provide all the information on the phenomena being studied. Meanwhile, qualitative research allows the researcher to participate in the observation of the object of study. Both methods have their advantages and their weaknesses. Conclusions: The investigator must be careful when designing research and choose the method that provides more reliability to the study conducted. The combination of both methods seems to be the most acceptable option and reduce the possibility of bias.
377 citations
TL;DR: Hand-held dynamometry has good to excellent reliability and validity for most measures of isometric lower limb strength and power in a healthy population, particularly for proximal muscle groups.
Abstract: © 2015 Mentiplay et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Introduction Hand-held dynamometry (HHD) has never previously been used to examine isometric muscle power. Rate of force development (RFD) is often used for muscle power assessment, however no consensus currently exists on the most appropriate method of calculation. The aim of this study was to examine the reliability of different algorithms for RFD calculation and to examine the intra-rater, inter-rater, and inter-device reliability of HHD as well as the concurrent validity of HHD for the assessment of isometric lower limb muscle strength and power. Methods 30 healthy young adults (age: 23±5yrs, male: 15) were assessed on two sessions. Isometric muscle strength and power were measured using peak force and RFD respectively using two HHDs (Lafayette Model-01165 and Hoggan microFET2) and a criterion-reference Kin-Com dynamometer. Statistical analysis of reliability and validity comprised intraclass correlation coefficients (ICC), Pearson correlations, concordance correlations, standard error of measurement, and minimal detectable change. Results Comparison of RFD methods revealed that a peak 200ms moving window algorithm provided optimal reliability results. Intra-rater, inter-rater, and inter-device reliability analysis of peak force and RFD revealed mostly good to excellent reliability (coefficients o 0.70) for all muscle groups. Concurrent validity analysis showed moderate to excellent relationships between HHD and fixed dynamometry for the hip and knee (ICCs o 0.70) for both peak force and RFD, with mostly poor to good results shown for the ankle muscles (ICCs = 0.31-0.79). \Conclusions Hand-held dynamometry has good to excellent reliability and validity for most measures of isometric lower limb strength and power in a healthy population, particularly for proximal muscle groups. To aid implementation we have created freely available software to extract these variables from data stored on the Lafayette device. Future research should examine the reliability and validity of these variables in clinical populations.
287 citations
TL;DR: In this article, the authors present a survey on the development and use of Artificial Neural Network (ANN) models in structural reliability analysis, identifying the different types of ANNs, the methods of structural reliability assessment that are typically used, the techniques proposed for ANN training set improvement and also some applications of ANN approximations to structural design and optimization problems.
278 citations
TL;DR: The TESTEX scale is a new, reliable tool, specific to exercise scientists, that facilitates a comprehensive review of exercise training trials.
Abstract: Introduction:Several established tools are available to assess study quality and reporting of randomized controlled trials; however, these tools were designed with clinical intervention trials in mind. In exercise training intervention trials some of the traditional study quality criteria, s
TL;DR: A systematic review of the validity evidence for checklists and GRSs in the context of simulation‐based assessment of health professionals finds that both types of scale types should be considered for use in clinical practice.
Abstract: Context
The relative advantages and disadvantages of checklists and global rating scales (GRSs) have long been debated. To compare the merits of these scale types, we conducted a systematic review of the validity evidence for checklists and GRSs in the context of simulation-based assessment of health professionals.
Methods
We conducted a systematic review of multiple databases including MEDLINE, EMBASE and Scopus to February 2013. We selected studies that used both a GRS and checklist in the simulation-based assessment of health professionals. Reviewers working in duplicate evaluated five domains of validity evidence, including correlation between scales and reliability. We collected information about raters, instrument characteristics, assessment context, and task. We pooled reliability and correlation coefficients using random-effects meta-analysis.
Results
We found 45 studies that used a checklist and GRS in simulation-based assessment. All studies included physicians or physicians in training; one study also included nurse anaesthetists. Topics of assessment included open and laparoscopic surgery (n = 22), endoscopy (n = 8), resuscitation (n = 7) and anaesthesiology (n = 4). The pooled GRS–checklist correlation was 0.76 (95% confidence interval [CI] 0.69–0.81, n = 16 studies). Inter-rater reliability was similar between scales (GRS 0.78, 95% CI 0.71–0.83, n = 23; checklist 0.81, 95% CI 0.75–0.85, n = 21), whereas GRS inter-item reliabilities (0.92, 95% CI 0.84–0.95, n = 6) and inter-station reliabilities (0.80, 95% CI 0.73–0.85, n = 10) were higher than those for checklists (0.66, 95% CI 0–0.84, n = 4 and 0.69, 95% CI 0.56–0.77, n = 10, respectively). Content evidence for GRSs usually referenced previously reported instruments (n = 33), whereas content evidence for checklists usually described expert consensus (n = 26). Checklists and GRSs usually had similar evidence for relations to other variables.
Conclusions
Checklist inter-rater reliability and trainee discrimination were more favourable than suggested in earlier work, but each task requires a separate checklist. Compared with the checklist, the GRS has higher average inter-item and inter-station reliability, can be used across multiple tasks, and may better capture nuanced elements of expertise.
TL;DR: A shortened version of the original 23-item Kansas City Cardiomyopathy Questionnaire, the KCCQ-12, is developed to capture symptom frequency, physical and social limitations, and quality of life impairment as a result of heart failure.
Abstract: Background— There is a growing demand to collect patients’ experiences of their health status (their symptoms, function, and quality of life) in clinical trials, quality assessment initiatives, and in routine clinical care. In heart failure, the 23-item, disease-specific Kansas City Cardiomyopathy Questionnaire (KCCQ) has been shown to be valid, reliable, sensitive to clinical change, and prognostic of both clinical events and costs. However, its use has been limited, in part, by its length. We sought to develop a shortened version of the instrument that maintains the psychometric properties of the full KCCQ.
Methods and Results— Using data from 3 clinical studies incorporating 4168 patients, we derived and validated a 12-item KCCQ, the KCCQ-12, to capture symptom frequency, physical and social limitations, and quality of life impairment as a result of heart failure, as well as an overall summary score. The KCCQ-12 scores had high correlations with the original scales (>0.93 for all scales in all clinical settings), high test–retest reliability (>0.76 for all domains), high responsiveness (16–31 point improvements after discharge from hospitalization; standardized response mean =0.61–1.12), and comparable prognostic significance and interpretation of clinically important differences as compared with the full KCCQ.
Conclusion— The KCCQ-12 is a shorter version of the original 23-item instrument that should be more feasible to implement while preserving the psychometric properties of the full instrument.
TL;DR: An update of results regarding an novative critical appraisal tool, called the ‘Mixed ethods Appraisal Tool’ (MMAT), which were published two papers in the International Journal of Nursing udies, and a need for additional supporting evidence for the MMAT.
TL;DR: In this article, the authors present a statistical approach based on binomial logic to critiquing and supporting the practice of semi-structured interview research in the building and energy field.
Abstract: Research in building energy consumption often uses semi-structured interviews to produce qualitative data on consumer beliefs, attitudes, practices and skills. A survey of 54 recent papers in six prominent building and energy journals shows that the samples are typically small, but inferences are often made for interventions in the light of the findings, on the assumption that these are somehow transferable to wider populations. It is often asked ‘how many interviews are enough’ to produce reliable results. Theoretical literature on this theme has avoided a straightforward statistical critique, and justified the practice with appeals to precedent, the special nature of qualitative personal data, and a limited pool of empirical work. This paper reviews this literature and presents a statistical approach, based on binomial logic, to critiquing and supporting the practice of semi-structured interview research in the building and energy field. The approach developed offers a set of straightforward criteria which researchers can use to estimate the reliability of their findings and inferences from the qualitative data produced in semi-structured interviews.
TL;DR: A new learning function based on information entropy is proposed that can help select the next point effectively and add it to the design of experiments to update the metamodel in a more efficient way.
Abstract: In structural reliability, an important challenge is to reduce the number of calling the performance function, especially a finite element model in engineering problem which usually involves complex computer codes and requires time-consuming computations. To solve this problem, one of the metamodels, Kriging is then introduced as a surrogate for the original model. Kriging presents interesting characteristics such as exact interpolation and a local index of uncertainty on the prediction which can be used as an active learning method. In this paper, a new learning function based on information entropy is proposed. The new learning criterion can help select the next point effectively and add it to the design of experiments to update the metamodel. Then it is applied in a new method constructed in this paper which combines Kriging and Line Sampling to estimate the reliability of structures in a more efficient way. In the end, several examples including non-linearity, high dimensionality and engineering problems are performed to demonstrate the efficiency of the methods with the proposed learning function.
TL;DR: The large number of available batteries can be beneficial to the clinician or researcher; however, care should be taken in order to choose the correct battery for each application.
Abstract: Objective:This article is a review of computerized tests and batteries used in the cognitive assessment of older adults.Method:A literature search on Medline followed by cross-referencing yielded a total of 76 citations.Results:Seventeen test batteries were identified and categorized according to their scope. Computerized adaptive testing (CAT) and the Cambridge Cognitive Examination CAT battery as well as 3 experimental batteries and an experimental test are discussed in separate sections. All batteries exhibit strengths associated with computerized testing such as standardization of administration, accurate measurement of many variables, automated record keeping, and savings of time and costs. Discriminant validity and test–retest reliability were well documented for most batteries while documentation of other psychometric properties varied.Conclusion:The large number of available batteries can be beneficial to the clinician or researcher; however, care should be taken in order to choose the correct bat...
TL;DR: It is argued for the use of Big Data as complementary audit evidence using the audit evidence criteria framework and cost-benefit analysis for sufficiency, reliability, and relevance considerations are provided.
Abstract: SYNOPSIS In this paper we argue for the use of Big Data as complementary audit evidence. We evaluate the applicability of Big Data using the audit evidence criteria framework and provide cost-benefit analysis for sufficiency, reliability, and relevance considerations. Critical challenges, including integration with traditional audit evidence, information transfer issues, and information privacy protection, are discussed and possible solutions are provided.
26 Jul 2015
TL;DR: Technical problems and controversial findings in healthy people and some psychiatric disorders reveal that the reliability of MDA as a biomarker of oxidative stress n eeds to be re-evaluated by experts.
Abstract: Despite very wide variations of malondialdehyde (MDA) concentrations in biological samples, it is still used as a biomarker of oxidative stress in clinical investigations. In the current perspective study, we aimed to summarize a number of critical analytical points for determination of MDA. Technical problems and controversial findings in healthy people and some psychiatric disorders reveal that the reliability of MDA as a biomarker of oxidative stress n eeds to be re-evaluated by experts.
TL;DR: In this paper, the authors present a research framework and a straightforward guide for the use of IPA, which can be used to guide researchers through the various stages of the IPA process.
10 Aug 2015
TL;DR: Experimental results on two real-world datasets show that FaitCrowd can significantly reduce the error rate of aggregation compared with the state-of-the-art multi-source aggregation approaches due to its ability of learning topical expertise from question content and collected answers.
Abstract: In crowdsourced data aggregation task, there exist conflicts in the answers provided by large numbers of sources on the same set of questions. The most important challenge for this task is to estimate source reliability and select answers that are provided by high-quality sources. Existing work solves this problem by simultaneously estimating sources' reliability and inferring questions' true answers (i.e., the truths). However, these methods assume that a source has the same reliability degree on all the questions, but ignore the fact that sources' reliability may vary significantly among different topics. To capture various expertise levels on different topics, we propose FaitCrowd, a fine grained truth discovery model for the task of aggregating conflicting data collected from multiple users/sources. FaitCrowd jointly models the process of generating question content and sources' provided answers in a probabilistic model to estimate both topical expertise and true answers simultaneously. This leads to a more precise estimation of source reliability. Therefore, FaitCrowd demonstrates better ability to obtain true answers for the questions compared with existing approaches. Experimental results on two real-world datasets show that FaitCrowd can significantly reduce the error rate of aggregation compared with the state-of-the-art multi-source aggregation approaches due to its ability of learning topical expertise from question content and collected answers.
TL;DR: Huang et al. as mentioned in this paper examined the validity of the infrequency approach to detecting insufficient effort responding and assess participant reactions to such an approach and found that surveys that contained infrequency items did not lead to more negative reactions than did surveys that did not contain such items.
Abstract: Insufficient effort responding (IER), which occurs due to a lack of motivation to comply with survey instructions and to correctly interpret item content, represents a serious problem for researchers and practitioners who employ survey methodology (Huang et al. 2012). Extending prior research, we examine the validity of the infrequency approach to detecting IER and assess participant reactions to such an approach. Two online surveys (Studies 1 and 2) completed by employed undergraduates were utilized to assess the validity of the infrequency approach. An on-line survey of paid participants (Study 3) and a paper-and-pencil survey in an organization (Study 4) were conducted to evaluate participant reactions, using random assignment into survey conditions that either did or did not contain infrequency items. Studies 1 and 2 provided evidence for the reliability, unidimensionality, and criterion-related validity of the infrequency scales. Study 3 and Study 4 showed that surveys that contained infrequency items did not lead to more negative reactions than did surveys that did not contain such items. The current findings provide evidence of the effectiveness and feasibility of the infrequency approach for detecting IER, supporting its application in low-stakes organizational survey contexts. The current studies provide a more in-depth examination of the infrequency approach to IER detection than had been done in prior research. In particular, the evaluation of participant reactions to infrequency scales represents a novel contribution to the IER literature.
TL;DR: A robust approach based on the technique of design for six sigma is presented for the system-level design optimization of drive systems to improve the reliability and quality of products in batch production in this work.
Abstract: A system-level design optimization method under the framework of a deterministic approach was presented for electrical drive systems in our previous work, in which not only motors but also the integrated control schemes were designed and optimized to achieve good steady and dynamic performances. However, there are many unavoidable uncertainties (noise factors) in the industrial manufacturing process, such as material characteristics and manufacturing precision. These will result in big fluctuations for the product's reliability and quality in mass production, which are not investigated in the deterministic approach. Therefore, a robust approach based on the technique of design for six sigma is presented for the system-level design optimization of drive systems to improve the reliability and quality of products in batch production in this work. Meanwhile, two system-level optimization frameworks are presented for the proposed method, namely, single-level (only at the system level) and multilevel frameworks. Finally, a drive system is investigated as an example, and detailed results are presented and discussed. It can be found that the reliability and quality levels of the investigated drive system have been greatly increased by using the proposed robust approach.
Patent•
30 Nov 2015
TL;DR: In this paper, a method and apparatus for unmanned aerial vehicles (UAVs) with improved reliability is presented. But the method is limited to the case of UAVs.
Abstract: The present invention provides methods and apparatus for unmanned aerial vehicles (UAVs) with improved reliability. According to one aspect of the invention, interference experienced by onboard sensors from onboard electrical components is reduced. According to another aspect of the invention, user-configuration or assembly of electrical components is minimized to reduce user errors.
TL;DR: The present study seeks to identify the data preprocessing pipeline that optimizes rs-fMRI data and maximize result reliability, while retaining the unique features that characterize distinct groups, and examines how these metrics are influenced by bandpass filter selection and noise regression in four datasets.
TL;DR: The proposed Reliability-based Trust-aware Collaborative Filtering method provides a dynamic mechanism to construct trust network of the users based on the proposed reliability measure to improve the reliability and also the accuracy of the predictions.
Abstract: We proposed a trust-based collaborative filtering method called RTCF.A trust based reliability measure is proposed to evaluate quality of predicted rates.A new mechanism is proposed to reconstruct the trust network.Experiments were performed on two real-world datasets.The results show that our method outperformed several state-of-the-art methods. Recommender systems (RSs) are programs that apply knowledge discovery techniques to make personalized recommendations for user's information on the web. In online sharing communities or e-commerce sites, trust is an important mechanism to improve relationship among users. Trust-aware recommender systems are techniques to make use of trust statements and user personal data in social networks. The accuracy of ratings prediction in RSs is one of the most important problems. In this paper, a Reliability-based Trust-aware Collaborative Filtering (RTCF) method is proposed to improve the accuracy of the trust-aware recommender systems. In the proposed method first of all, the initial trust network of the active user is constructed by using combination of the similarity values and the trust statements. Then, an initial rate is predicted for an unrated item of the user. In the next step, a novel trust based reliability measure is proposed to evaluate the quality of the predicted rate. Then, a new mechanism is performed to reconstruct the trust network for those of the users with lower reliability value than a predefined threshold. Finally, the final rate of the unrated item is predicted based on the new trust network of the user. In other words, the proposed method provides a dynamic mechanism to construct trust network of the users based on the proposed reliability measure. Therefore, the proposed method leads to improve the reliability and also the accuracy of the predictions. Experimental results performed on two real-world datasets including; Epinions and Flixster, demonstrated that the proposed method achieved higher accuracy and also obtained reasonable user and rate coverage compared to several state-of-the-art recommender system methods.
TL;DR: This work reviews tools that meet established reliability and validity metrics for youth and adult mental health for the most prevalent mental health disorders to provide a clinical guide and reference for the selection of assessment tools for public sector settings.
TL;DR: In this paper, a numerical strategy for the efficient estimation of set-valued failure probabilities, coupling Monte Carlo with optimization methods, is presented in order to both speed up the reliability analysis, and provide a better estimate for the lower and upper bounds of the failure probability.
TL;DR: In this article, a small survey was conducted on 28 vocational college students enrolled in the Building Construction course and three sets of research instruments were developed in order to produce empirical evidence of validity and reliability using the Rasch Model.